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Consumption of added sugars From a public health perspective bipolar depression in children buy genuine amitriptyline line, it is Patterns are based on consuming foods can make it diffcult for individuals to meet important to identify the calories that are in their nutrient-dense forms winter depression symptoms uk buy amitriptyline 50 mg. Naturally occurring sugars 9435 mood disorder buy amitriptyline 25 mg on line, inform guidance on limits from calories from fat forms depression webmd purchase amitriptyline on line amex, see Appendix 6) anxiety questionnaire for adults cheap 50 mg amitriptyline with amex. For nearly [21] such as those in fruit or milk depression test dansk generic amitriptyline 50 mg with amex, are not added added sugars, solid fats, alcohol, or other all calorie levels, most of the calories in sugars. In the 2,000-calorie this recommendation is a target to help many calories are available to select foods pattern, the limit for other uses is 270 the public achieve a healthy eating pattern, from a food group that are not in nutrientcalories and in the 2,800-calorie pattern, which means meeting nutrient and food dense forms. As discussed in the next 400 calories (see Appendix 3, Appendix 4, group needs through nutrient-dense food portion of the chapter, additional constraints and Appendix 5). Calories up to the limit and beverage choices and staying within apply related to other dietary components for the specifc pattern can be used to calorie limits. This target also is informed or solid fats) or to eat more than the In addition to the food groups, it is important by national data on intakes of calories recommended amount of nutrient-dense to consider other food components when from added sugars, which as discussed in foods. The Chapter 2, account on average for almost from alcoholic beverages should also be components discussed here include 270 calories, or more than 13 percent of accounted for within this limit to keep total added sugars, saturated fats, trans fats, calories per day in the U. For each component, information is provided As discussed in Chapter 2, in contrast on how the component relates to eating to the healthy choices that make up the patterns and outlines considerations related Patterns, foods from most food groups as to the component. See Chapter 2 they are typically consumed in the United for a further discussion of each of these States are not in nutrient-dense forms. Hidden Components in Eating Patterns Many of the foods and beverages we eat contain sodium, saturated fats, and added sugars. Making careful choices, as in this example, keeps amounts of these components within their limits while meeting nutrient needs to achieve a healthy eating pattern. As discussed in not exceed the acceptable daily intake, even pattern with enough foods from all food Chapter 2, the two main sources of added for high consumers of each substance. There is room on calories for other uses are more than 10 for Americans to include limited amounts percent per day. The recommendation to limit of added sugars in their eating patterns, added sugars to no more than 10 percent of including to improve the palatability of Saturated Fats, Trans Fats, calories is a target that applies to all calorie some nutrient-dense foods, such as fruits & Cholesterol levels to help individuals move toward and vegetables that are naturally tart. Healthy eating Healthy Intake: Intake of saturated patterns can accommodate other nutrientAlthough the evidence for added sugars fats should be limited to less than 10 dense foods with small amounts of added and health outcomes is still developing, percent of calories per day by replacing sugars, such as whole-grain breakfast the recommendation to limit calories from them with unsaturated fats and while cereals or fat-free yogurt, as long as added sugars is consistent with research keeping total dietary fats within the agecalories from added sugars do not exceed examining eating patterns and health. Individuals include lower intake of sources of added It should be noted that replacing added 2 years and older therefore have no sugars are associated with reduced risk sugars with high-intensity sweeteners may dietary requirement for saturated fats. Based on the available shows that replacing saturated fats not necessarily to an isolated aspect of scientifc evidence, these high-intensity with polyunsaturated fats is associated the diet. Page 31 — 2015-2020 Dietary Guidelines for Americans Chapter 1• for monounsaturated fats is not as strong in margarines, and by limiting other solid Dietary Cholesterol as the evidence base for replacement fats. A number of studies have observed the body uses cholesterol for physiological with polyunsaturated fats. Trans fatty dietary cholesterol, such as fatty meats and fats in the diet should be replaced with acids produced this way are referred to as high-fat dairy products, are also higher in polyunsaturated and monounsaturated fats. Artifcial trans fatty acids are limited in saturated fats, and because of the the main sources of saturated fats in the U. Although some saturated fats are the amounts of artifcial trans fats in many cholesterol across the 12 calorie levels. Healthy foods in recent years, these fats can still Current average intake of dietary cholesterol eating patterns can accommodate nutrientbe found in some processed foods, such as among those 1 year and older in the United dense foods with small amounts of saturated some desserts, microwave popcorn, frozen States is approximately 270 mg per day. Because natural trans earlier, eating patterns consist of multiple, Individuals should limit intake of trans fats fats are present in dairy products and meats interacting food components and the to as low as possible by limiting foods in only small quantities and these foods can relationships to health exist for the overall that contain synthetic sources of trans be important sources of nutrients, these foods eating pattern, not necessarily to an isolated fats, such as partially hydrogenated oils do not need to be eliminated from the diet. It is low in saturated fats and rich in potassium, calcium, and magnesium, as well as dietary fber and protein. It also is lower in sodium than the typical American diet, and includes menus with two levels of sodium, 2,300 and 1,500 mg per day. Caffeine Caffeine is not a nutrient; it is a dietary component that functions in the body as a stimulant. If caffeine is added to a food, it must be included in the listing of ingredients on the food label. Caffeinated coffee beverages include drip/brewed coffee (12 mg/f oz), instant coffee (8 mg/f oz), espresso (64 mg/f oz), and specialty beverages made from coffee or espresso, such as cappuccinos and lattes. Amounts of caffeine in other beverages such as brewed black tea (6 mg/f oz), brewed green tea (2-5 mg/f oz), and caffeinated soda[26] (1-4 mg/f oz) also vary. Beverages within the energy drinks category have the greatest variability (3-35 mg/f oz). Moderate coffee consumption (three to fve 8-oz cups/day or providing up to 400 mg/day of caffeine) can be incorporated into healthy eating patterns. This guidance on coffee is informed by strong and consistent evidence showing that, in healthy adults, moderate coffee consumption is not associated with an increased risk of major chronic diseases. However, individuals who do not consume caffeinated coffee or other caffeinated beverages are not encouraged to incorporate them into their eating pattern. Limited and mixed evidence is available from randomized controlled trials examining the relationship between those energy drinks which have high caffeine content and cardiovascular risk factors and other health outcomes. In addition, caffeinated beverages, such as some sodas or energy drinks, may include calories from added sugars, and although coffee itself has minimal calories, coffee beverages often contain added calories from cream, whole or 2% milk, creamer, and added sugars, which should be limited. The same considerations apply to calories added to tea or other similar beverages. Those who choose to drink alcohol should be cautious about mixing caffeine and alcohol together or consuming them at the same time; see Appendix 9. In addition, women who are capable of becoming pregnant or who are trying to , or who are pregnant, and those who are breastfeeding should consult their health care providers for advice concerning caffeine consumption. Page 33 — 2015-2020 Dietary Guidelines for Americans Chapter 1• regarding the dose-response relationship linear dose-response relationship between Considerations: As a food ingredient, between dietary cholesterol and blood increased sodium intake and increased blood sodium has multiple uses, such as in curing cholesterol levels. In addition, moderate meat, baking, thickening, enhancing favor available for a quantitative limit for dietary evidence suggests an association between (including the favor of other ingredients), cholesterol specifc to the Dietary Guidelines. A few foods, found in foods across the food supply, including notably egg yolks and some shellfsh, Calorie intake is highly associated with mixed dishes such as burgers, sandwiches, are higher in dietary cholesterol but not sodium intake. Eggs and shellfsh can be beverages people consume, the more meat, poultry, and seafood dishes; and soups. Because Multiple strategies should be implemented choices within and across the subgroup children have lower calorie needs than to reduce sodium intake to the recommended recommendations of the protein foods group. Everyone Has a Role for children younger than 14 years of Sodium in Supporting Healthy Eating Patterns). The Dietary Guidelines does not Guidelines Advisory Committees, is that blood pressure is found in children as well. If alcohol 3,440 mg per day (see Chapter 2), is too Adults with prehypertension and hypertension is consumed, it should be in moderation—up high and should be reduced. Healthy eating would particularly beneft from blood pressure to one drink per day for women and up to patterns limit sodium to less than 2,300 mg lowering. For these individuals, further two drinks per day for men—and only by per day for adults and children ages 14 years reduction to 1,500 mg per day can result adults of legal drinking age. Sodium is an essential nutrient blood pressure, every incremental decrease alcohol that may be consumed, the Dietary and is needed by the body in relatively in sodium intake that moves toward Guidelines includes drink-equivalents. Food Surveys Research Group, Beltsville Human Nutrition Research Center, Agricultural Research Service, U. Examples of Composition of the Healthy Mediterranean-Style Other Healthy & Healthy Vegetarian Eating Patterns at the Eating Patterns [a] 2,000-Calorie Level, With Daily or Weekly Amounts the U. There are many ways Vegetables 2½ c-eq/day 2½ c-eq/day to consume a healthy eating pattern, Dark Green 1½ c-eq/week 1½ c-eq/week and the evidence to support multiple approaches has expanded over time. Red & Orange 5½ c-eq/week 5½ c-eq/week the Healthy Mediterranean-Style [c] Legumes (Beans & Peas) 1½ c-eq/week 3 c-eq/week Eating Pattern and Healthy Vegetarian Eating Pattern, which were developed Starchy 5 c-eq/week 5 c-eq/week by modifying the Healthy U. Quantity 2,000 calorie level for each Pattern is equivalents for each food group are defned in Appendix 3. Amounts will vary for those who need less than 2,000 shown here as an example (Table 1-2). Healthy Mediterranean[c]Vegetarian patterns include 1½ cups per week of legumes as a vegetable subgroup, and an additional 6 oz-eq (1½ cups) per week of legumes as a protein food. The total amount is shown here as legumes in the vegetable Style Eating Pattern group. Pattern (Appendix 4) was designed by [e]Assumes food choices to meet food group recommendations are in nutrient-dense forms. Most calorie patterns do not have enough calories available after meeting food group needs to consume 10 percent of calories from added sugars and Academies Press; 2002. Page 35 — 2015-2020 Dietary Guidelines for Americans Chapter 1• Pattern, taking into account food group intakes from studies examining the associations between MediterraneanStyle eating patterns and health. The Healthy Mediterranean-Style Eating Pattern contains more fruits and seafood and less dairy than does the Healthy U. The healthfulness of the Healthy Mediterranean-Style Pattern was evaluated based on its similarity to Mediterranean-Style patterns described in studies with positive health outcomes rather than on meeting specifed nutrient standards. However, nutrient content of the Pattern was assessed and found to be similar to the Healthy U. Calcium and vitamin D are Style Pattern, but is somewhat higher lower because the amounts of dairy were in calcium and dietary fber and lower decreased, as shown in Appendix 4, to in vitamin D, due to differences in the more closely match data from studies of foods included in the protein foods group, Mediterranean-Style eating patterns. The Healthy Vegetarian enhance eating and physical activity Eating Pattern was developed taking into patterns. At the core of this guidance is the and provides recommendations to importance of consuming overall healthy meet the Dietary Guidelines for those eating patterns, including vegetables, who follow a vegetarian pattern. It contains guidance into practice are provided by no meats, poultry, or seafood, and is the Healthy U. Cut back on is meeting or exceeding total ollowing healthy eating patterns is foods and beverages higher in these grain and total protein foods vital to health. This chapter provides a components to amounts that ft within recommendations, but, as discussed F snapshot of current eating patterns of healthy eating patterns. Choose nutrient-dense foods describes shifts that are needed to align and beverages across and within all. In food groups in place of less healthy recommendations for added sugars, some cases, the news is good—for certain choices. Support healthy eating patterns for over time, in comparison to calorie needs, other aspects of the diet are far from the all. Everyone has a role in helping to is best evaluated by measuring body recommendations. The high percentage of the beneft from shifting food choices both in multiple settings nationwide, from population that is overweight or obese within and across food groups and from home to school to work to communities. Some shifts that are needed are the chapter includes quantitative the Introduction, Table I-1, more than minor and can be accomplished by making information on intakes and common sources two-thirds of all adults and nearly onesimple substitutions, while others will of food groups, their subgroups, and other third of all children and youth in the United require greater effort to accomplish. The chapter also includes strategies to help shift current eating patterns Current eating patterns can be moved About this Chapter toward the healthy patterns described toward healthier eating patterns by making in Chapter 1. Making this chapter focuses on the to support individuals in their effort to these shifts can help support a healthy fourth Dietary Guideline: make shifts are discussed in greater body weight, meet nutrient needs, and detail in Chapter 3. Choose a intakes of the food groups and other healthy eating pattern at an appropriate dietary components for age-sex groups calorie level to help achieve and Current Eating Patterns and show that, in some cases, individuals maintain a healthy body weight, support in the United States are close to meeting recommendations, nutrient adequacy, and reduce the risk of but in others, more substantial change is chronic disease. They also provide examples of consumed by many in the United States foods commonly consumed. To meet nutrient As shown in Figure 2-1, when compared groups and other dietary components are needs within calorie limits, choose to the Healthy U. Limit calories from added sugars two ways: and saturated fats and reduce sodium intake. For most, those represented by the orange sections of the bars, shifting toward the center line will improve their eating pattern. Changing Physical Empower People To Make Activity Patterns Healthy Shifts for a Healthy Making changes to eating patterns can be overwhelming. That’s why it’s important to emphasize that every food choice is an Lifestyle opportunity to move toward a healthy eating pattern. Small shifts in Current Physical Activity: food choices—over the course of a week, a day, or even a meal— Only 20 percent of adults meet the can make a big difference. Here are some ideas for realistic, small Physical Activity Guidelines for aerobic shifts that can help people adopt healthy eating patterns. Males are more likely to report doing regular physical activity compared to females (24% of males versus 17% of females meet recommendations), and this difference is more pronounced between adolescent boys and girls High Calorie Snacks Nutrient-Dense Snacks (30% of males versus 13% of females meet recommendations). Despite evidence that increments of physical activity as short as 10 minutes at a time can be benefcial, about 30 percent of adults report engaging in no leisure time physical activity. Disparities also Fruit Products with Added Sugars Fruit exist; individuals with lower income and those with lower educational attainment have lower rates of physical activity and are more likely to not engage in leisure time physical activity. Overall, physical activity associated Refned Grains Whole Grains with work, home, and transportation has declined in recent decades and can be attributed to less active occupations; reduced physical activity for commuting to work, school, or for errands; and increased sedentary behavior often Snacks with Added Sugars Unsalted Snacks associated with television viewing and other forms of screen time. Solid Fats Oils Shift Physical Activity Choices: Most individuals would beneft from making shifts to increase the amount of physical activity they engage in each week. Individuals would also beneft from limiting screen time and decreasing the amount Beverages with Added Sugars No-Sugar-Added Beverages of time spent being sedentary. Average Daily Food Group Intakes by Recommended Intake Ranges Age-Sex Groups, Compared to Ranges of Average Intake Recommended Intake Vegetables 4 4 3 3 2 2 1 1 0 0 1 4 9 14 19 31 51 71 + 1 4 9 14 19 31 51 71 + to to to to to to to to to to to to to to 3 8 13 18 30 50 70 3 8 13 18 30 50 70 Males (years) Females (years) Fruits 3 3 2. Food Groups across age-sex groups in comparison A Closer Look at to recommended intake levels. Current Intakes & the following sections describe total Vegetable consumption relative to current intakes for each of the food Recommended Shifts recommendations is lowest among boys groups and for oils, and the leading food ages 9 to 13 years and girls ages 14 to categories contributing to this total. Vegetable intakes relative to also describe the shifts in food choices foods in healthy eating patterns recommendations are slightly higher that are needed to meet recommendations should come from the food groups. Dense Versus Current Average Vegetable Subgroup Typical Choices in Intakes in Cup-Equivalents the Food Groups per Week by Age-Sex Groups, To stay within energy requirements while Compared to Ranges of meeting nutritional needs, food choices in each food group should be in nutrient-dense Recommended Intakes per Week forms. However, in many food groups, foods as they are typically eaten are not in nutrientDark Green Vegetables dense forms—they contain additional calories from components such as added sugars, added refned starches, solid fats, or a combination. Recommended Weekly Average Intake For example, in the dairy group, nutrient-dense Intake Ranges choices such as fat-free milk, plain fat-free yogurt, and low-fat cheese contain an average of about 80 calories per cup-equivalent. In 3 contrast, many dairy products that are typically consumed, such as whole milk, sweetened yogurt, and regular cheese, contain almost 150 calories per cup-equivalent.

Diseases

• Loose anagene syndrome
• Melkersson Rosenthal syndrome
• Pycnodysostosis
• Chondromatosis (benign)
• Purpura, thrombotic thrombocytopenic
• Revesz syndrome
• Trichodental syndrome
• Optic nerve coloboma with renal disease
• Nevus sebaceus of Jadassohn
• Hemophilic arthropathy

Is the beneft of postmastectomy irradiation limited to patients with four or more positive nodes depression love purchase amitriptyline on line amex, as recommended in international consensus reports? Locoregional radiation therapy in patients with high-risk breast cancer receiving adjuvant chemotherapy: 20-year results of the British Columbia randomized trial anxiety or depression generic amitriptyline 25mg with visa. Role of a 10-Gy boost in the conservative treatment of early breast cancer: results of a randomized clinical trial in Lyon mood disorder vs bipolar amitriptyline 25mg on line, France depression symptoms nz purchase amitriptyline 25 mg with mastercard. Clinical investigation: regional nodal failure patterns in breast cancer patients treated with mastectomy without radiotherapy anxiety leg pain buy cheap amitriptyline 50 mg online. Nodal ratios in node-positive breast cancer-longterm study to clarify discrepancy of role of supraclavicular and axillary regional radiotherapy depression bipolar support alliance purchase line amitriptyline. Radiotherapy after breast-preserving surgery in women with localized cancer of the breast. Avoiding axillary dissection in breast cancer surgery: a randomized trial to assess the role of axillary radiotherapy. Should adjuvant radiotherapy to the supraclavicular fossa be routinely given in patients with breast conservative treatment? Palliative Care Needs Assessment Guidance, National Clinical Programme for Palliative Care. Evidence on the cost and cost-effectiveness of palliative care: A literature review. American Society of Clinical Oncology provisional clinical opinion: the integration of palliative care into standard oncology care. Economic burden of cancer across the European Union: a population-based cost analysis. The behaviour change wheel: A new method for characterising and designing behaviour change interventions. Comparing fve alternative methods of breast reconstruction surgery: a cost-effectiveness analysis. A systematic review and methodological evaluation of published cost-effectiveness analyses of aromatase inhibitors versus tamoxifen in early stage breast cancer. Economic consequence of local control with radiotherapy: cost analysis of internal mammary and medial supraclavicular lymph node radiotherapy in breast cancer. Cost-Beneft Analysis of Endocrine Therapy in the Adjuvant Setting for Postmenopausal Patients with Hormone Receptor-Positive Breast Cancer, Based on Survival Data and Future Prices for Generic Drugs in the Context of the German Health Care System. Hypofractionated radiation therapy for early stage breast cancer: outcomes, toxicities, and cost analysis. Examining the cost-effectiveness of radiation therapy among older women with favorable-risk breast cancer. Effectiveness and cost-effectiveness of sentinel lymph node biopsy compared with axillary node dissection in patients with early-stage breast cancer: a decision model analysis. Cost-effectiveness of contralateral prophylactic mastectomy versus routine surveillance in patients with unilateral breast cancer. Department of Health, Hawkins House, Hawkins Street, Dublin, Ireland Tel: +353 1 6354000. Deep Convolutional Neural Networks for Breast Cancer Histology Image Analysis Alexander Rakhlin, Alexey Shvets, Vladimir Iglovikov,1 2 3 and Alexandr A. Kalinin4 1 National Research University of Electronic Technology, Moscow, Russia rakhlin@gmx. Early diagnostics significantly increases the chances of correct treatment and survival, but this process is tedious and often leads to a disagreement between pathologists. Computer-aided diagnosis systems showed potential for improving the diagnostic accuracy. In this work, we develop the computational approach based on deep convolution neural networks for breast cancer histology image classification. Our approach utilizes several deep neural network architectures and gradient boosted trees classifier. To our knowledge, this approach outperforms other common methods in automated histopathological image classification. Breast tissue biopsies allow the pathologists to histologically assess the microscopic structure and elements of the tissue. Histopathology aims to distinguish between normal tissue, non-malignant (benign) and malignant lesions (carcinomas) and to perform a prognostic evaluation [ ]. There are multiple types of breast carcinomas that embody characteristic tissue morphology, see Fig. Breast carcinomas arise from the mammary epithelium and cause a pre-malignant epithelial proliferation within the ducts, called ductal carcinoma in situ. Invasive carcinoma is characterized by the cancer cells gaining the capacity to break through the basal membrane of the duct walls and infiltrate into surrounding tissues [ ]. Morphology of tissue, cells, and subcellular compartments is regulated by complex biological mechanisms related to cell differentiation, development, and cancer [ ]. Traditionally, morphological assessment and tumor grading were visually performed by the pathologist, however, this process is tedious and subjective, causing inter-observer variations even among senior pathologists [, ]. There are many methods developed for the digital pathology image analysis, from rule-based to applications of machine learning [ ]. Recently, deep learning based approaches were shown to outperform conventional machine learning methods in many image analysis task, automating end-to-end processing [,, ]. Previous deep learning-based applications in histological microscopic image analysis have demonstrated their potential to provide utility in diagnosing breast cancer [,,, ]. In this paper, we present an approach for histology microscopy image analysis for breast cancer type classification. Dataset the image dataset is an extension of the dataset from [ ] and consists of H&E stain images (2048 × 1536 pixels). All the images are digitized with the same acquisition conditions, with a magnification of 200× and pixel size of 0. Each image is labeled with one of the four balanced classes: normal, benign, in situ carcinoma, and invasive carcinoma, where class is defined as a predominant cancer type in the image, see Fig. The goal of the challenge is to provide an automatic classification of each input image. Approach overview the limited size of the dataset (images of classes) poses a significant challenge for the training of a deep learning model [ ]. However, training these neural networks from scratch requires a large number of images, as training on a small dataset leads to overfitting i. A typical remedy in these circumstances is called fine-tuning when only a part of the pre-trained neural network is being fitted to a new dataset. However, in our experiments, fine-tuning approach did not demonstrate good performance on this task. Therefore, we employed a different approach known as deep convolutional feature representation [ ]. In this study, breast histology images are encoded with the state-of-the-art, general purpose networks to obtain sparse descriptors of low dimensionality (or). This unsupervised dimensionality reduction step significantly reduces the risk of overfitting on the next stage of supervised learning. Gradient boosting models are being extensively used in machine learning due to their speed, accuracy, and robustness against overfitting [ ]. Data pre-processing and augmentation To bring the microscopy images into a common space to enable improved quantitative analysis, we normalize the amount of H&E stained on the tissue as described in [ ]. Furthermore, in our initial experiments, we used different image scales, the original 2048 × 1536 pixels and downscaled in half to 1024 × 768 pixels. From the images of the original size we extract random crops of two sizes 800 × 800 and 1300×1300. From the downscaled images we extract crops of 400×400 pixels and 650 × 650 pixels. Then, the set of descriptors is combined through -norm pooling [ ] into a single descriptor: 1 ∑ 1 d = (d), =1 where the hyperparameter = 3 as suggested in [, ], is the number of crops, d is descriptor of a crop and d is pooled descriptor of the image. We remove fully connected layers from each model to allow the networks to consume images of an arbitrary size. In ResNetand InceptionV, we convert the last convolutional layer consisting of channels via GlobalAveragePooling into a one-dimensional feature vector with a length of. Augmentations increase the size of the dataset ×300 (patch sizes x encoders x color/affine augmentations). To prevent information leakage, all descriptors of the same image must be contained in the same fold. For each combination of the encoder, crop size and scale we train gradient boosting models with -fold cross-validation. In addition to obtaining cross-validated results, this allows us to increase the diversity of the models with limited data (bagging). At the cross-validation stage, we predict every fold only with the models not trained on this fold. For the test data, we similarly extract descriptors for each image and use them with all models trained for particular patch size and encoder. Table : Accuracy (%) and standard deviation for -class classification evaluated over folds via cross-validation. Finally, the importance of strong augmentation and model fusion we use is particularly evident from the Table. The fused model accuracy is by % higher than any of its individual constituents. Deep Learning for Breast Cancer Histology the standard deviation of the ensemble across folds is twice as low than the average standard deviation of the individual models. Moreover, all our results in the Table are slightly improved by averaging across seeded models. Conclusions In this paper, we propose a simple and effective method for the classification of H&E stained histological breast cancer images in the situation of very small training data (few hundred samples). On top of it, we apply highly accurate and prone to overfitting implementation of the gradient boosting algorithm. Unlike some previous works, we purposely avoid training neural networks on this amount of data to prevent suboptimal generalization. To our knowledge, the reported results are superior to the automated analysis of breast cancer images reported in literature [,, ]. Acknowledgments the authors thank the Open Data Science community [ ] for useful suggestions and other help aiding the development of this work. Guidelines for the early detection and screening of breast cancer / Edited by Oussama M. The designations employed and the presentation of the material in this publication do not imply the expression of any opinion whatsoever on the part of the World Health Organization concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. Dotted lines on maps represent approximate border lines for which there may not yet be full agreement. The mention of specific companies or of certain manufacturers’ products does not imply that they are endorsed or recommended by the World Health Organization in preference to others of a similar nature that are not mentioned. Errors and omissions excepted, the names of proprietary products are distinguished by initial capital letters. The World Health Organization does not warrant that the information contained in this publication is complete and correct and shall not be liable for any damages incurred as a result of its use. The named authors alone are responsible for the views expressed in this publication. Cover design and layout by Ahmad Hassanein Printed by Fikra Advertising Agency Contents Foreword. The estimated number of new cases each year is expected to rise from 10 million in 2002 to 15 million by 2025, with 60% of those cases occurring in developing countries. Breast cancer is the most common cancer in women in the Eastern Mediterranean Region and the leading cause of cancer mortality worldwide. There is geographic variation, with the standardized ageincidence rate being lower in developing than industrialized countries. Although the etiology of breast cancer is unknown, numerous risk factors may influence the development of this disease including genetic, hormonal, environmental, sociobiological and physiological factors. Over the past few decades, while the risk of developing breast cancer has increased in both industrialized and developing countries by 1%–2% annually, the death rate from breast cancer has fallen slightly. Researchers believe that lifestyle changes and advances in technology, especially in detection and therapeutic measures, are in part responsible for this decrease. Despite considerable social changes, women continue to be the focus of family life. The impact of breast cancer is therefore profound on both the woman diagnosed with the disease and her family. Their fear and anxiety over the eventual outcome of the illness may manifest itself through behavioural changes. The high incidence and mortality rates of breast cancer, as well as the high cost of treatment and limited resources available, require that it should continue to be a focus of attention for public health authorities and policy-makers. The costs and benefits of fighting breast cancer, including the positive impact that early detection and screening can have, need to be carefully weighed against other competing health needs. Ministry of Health officials need to formulate and implement plans that will effectively address the burden of the disease, including setting policies on the early detection and screening of breast cancer. Health care providers should also be involved in discussion of the issue and in developing programmes for the management of the disease. I hope these guidelines will support everyone involved in the battle against breast cancer in the Eastern Mediterranean Region. Studies have shown that most patients with breast cancer in the Region present for the first time at stages two and three, indicating the need for increased community awareness and early detection of the disease.

The study’s mPower app was downloaded by 48k people of whom 25% were eligible and participated in the study (12 anxiety relaxation techniques amitriptyline 50 mg without prescription. This is a nice example because it shows that people are willing to share data collected on their mobile devices for research purposes depression and relationships order amitriptyline online. In this example depression symptoms pregnancy order amitriptyline australia, the data being collected could also be a useful addition to an individual’s electronic health record anxiety rash symptoms cheap amitriptyline 25mg with visa. Finally mood disorder following cerebrovascular accident buy amitriptyline without a prescription, the implemented informed consent process both educated the individual on what they were consenting to regarding their data depression hyperbole and a half amitriptyline 50 mg discount, as well as giving an option to consent electronically, thus allowing their data to immediately be captured. These apps allow nearly instantaneous access to a live doctor, over mobile devices, anytime of day, every day of the week. Interestingly, the company is now expanding to Rwanda, where there is a serious shortage of doctors, yet a high penetration of smart phones. Online doctors’ appointments are likely to 23 appeal to many people who are already acclimated to the use of apps to fulfill personal needs. However, the potential dangers of sharing personal health information over such networked connections is a concern. In 2016, DeepMind launched several initiatives in the health care arena under its DeepMind Health Division [67]. For example, the problem discussed above with data access transparency may have led DeepMind to an accelerated application of blockchain-style technology for securing and tracking data access [72]. Basically, blockchain methodologies use a distributed database consisting of continuously updated (augmented) blocks which contain a linked list of all previous transactions [73]. In the case of health care, this encompasses all previous records of access to an individual data record including information about how the data was used and any additions or changes to the data record [74,75]. A second technology application that has emerged from DeepMind Health has many blockchainlike aspects [76,77]. Instead of blockchain, the DeepMind data audit system uses an approach based on Merkle Trees [78], a type of hash tree that allows secure verification of the contents of large data structures. DeepMind hopes to prototype the verifiable data audit system by the end of 2017 for eventual use in its Royal Hospital health care software environment [79]. Findings: ● Revolutionary changes in health and health care are already beginning in the use of smart devices to monitor individual health. Many of these developments are taking place outside of traditional diagnostic and clinical settings. This will promote the entry of all sorts of companies into this space, both meritorious and not. For instance, there are already many paid online services available that will help people interpret their Ancestry. This well studied gene has also been associated with numerous ills including contributing to plaque formation by damaging arterial walls and increasing the risks of clot formation. Here is a genetic variant that millions have been tested for (often inadvertently, via ancestry genetic testing) that sounds pretty scary. According to an exposé, [81] in one case the consultation costs $3000, and generally results in a prescription of exotic vitamin combinations only available through the site. Computer-aided automated skin cancer detection was demonstrated on biopsy-proven clinical images and tested against 21 dermatologists [82]. In parallel, online services already exist for remote dermatologist diagnosis of online-submitted images of skin moles [83]. We could imagine a scam service asking patients to submit self-taken skin mole images along with payment for an automated quack diagnosis in return, one that did not actually use any validated classification scheme. More likely, the methods used by any one company may be hidden or obscure, meaning the user has no way to judge the soundness of the company. Skinvision [83] is a new company based in the Netherlands for skin cancer melanoma detection where users download an app, take a picture for the app, and receive analysis, diagnosis, and tracking by the app. Very little information is provided about the methods used, other than Skinvision uses the mathematical theory of ‘fractal geometry’ for medical imaging to diagnose suspected melanoma and that the algorithm has been developed and tested in cooperation with dermatologists and checks for irregularities in color, texture, and shape of the lesion, although elsewhere in fine print the website acknowledges that our solution is not a diagnostic device. The threat of bogus web sites is diminished in the presence of trusted, credible resources. For example, information about cancer symptoms, diagnosis, and treatment options are provided by the American Cancer Society [84] and the Mayo Clinic [85]. It has been tremendously successful as a provider of news and information related to human health and well-being. Addressing this inevitable train wreck before it happens leads us to the following finding and recommendation. Websites, apps, and companies have already emerged that appear questionable based on information available. First is access to a smart platform such as a smartphone, and the second is access to the useful apps and devices. Recent data (2016) from Pew Research Center indicate 95% of Americans own a cellphone of some kind and 77% actually own a smartphone [87]. This is a sharp charge from 2011 where 83% of Americans owned a cellphone of some kind and only 35% owned a smartphone [88]. The distributions of cellphone and smartphone ownership for 2016 are given in Table 3. Ownership rates among men and women and different racial groups are quite similar. There are some differences across income and education levels, but overall rates are higher for every group than in 2011. There are differences in age groups with 100% of 18–29 year olds owning some sort of a cell phone and 92% owning a smartphone, compared to 95% and 49% in 2011. The elderly have lower adoption with only 80% of the 65+ age group owning a cellphone and only 42% owning a smartphone in 2016. Nonetheless, adoption is growing for the elderly as only 46% owned any sort of cellphone in 2011 and only 11% owned a smartphone. A Pew report from 2015 [89] pointed out that a growing number of Americans are using their smartphone as their primary broadband access device, with the largest groups with the behavior being non-white with lower education and income levels. It was also noted that more than half of all smartphone owners used their devices to access health information and do on-line banking. However, there may be inequitable differences among these demographic groups in the means, education levels, or physical capabilities needed to purchase, understand or use the tools. There are many issues of being able to develop and share datasets based on health and health care data. First of all is the cost of creating labeled data of high quality – this may require hiring expert image analysts, or providing additional testing (such as biopsies) to create labels. Other issues include the fact that the data may contain sensitive information about real people. Additionally, the culture in biology and life sciences, to include health care, is to closely protect one’s data that has typically been expensive and time intensive to collect. Few incentives exist to share this data until the primary researchers have squeezed all the results they can from their data. But first, there are overarching findings and recommendations associated with expanding the availability and access to comprehensive databases of health data. Several of the examples made use of the highly successful 29 ImageNet competition [92] results to initiate their deep learning algorithms. The two specific vehicles for this are crowdsourcing via online technical competitions and citizen science via online public engagement activities. The crowdsourcing competitions are able to engage top data scientists and programmers who are not health care domain experts. Some competitions have seen thousands of participants while others are purposefully limited to a select group of dozens of invited participants chosen from a pool of prior successful competitors. Monetary prizes are often given out to the top winners, and from typical totals as small as $10K through $100K even up to $1M. Leaderboards serve to motivate the competitors and discussion boards promote sharing of information sometimes leading up to collaborations in the competitions themselves. Contributed code is usually made public and serves both as a benchmark and to move the field forward. Crowdsourcing is motivated by the fact that while there are numerous and varied strategies that can be applied to any predictive modeling task, it is impossible to know at the outset which technique will be most effective. Kaggle [93] is a popular, successful, and leading online data science competition host with over 760,000 members around the world and hundreds of completed competitions in a variety of fields. One of the most successful health competitions to date was held in 2016-2017, run by Kaggle and Data Science Bowl [94] with support from over two dozen organizations. Competitors used anonymized, high-resolution lung scans from hundreds of patients provided by the National Cancer Institute. But the challenge is distinguishing the mutations that contribute to tumor growth (drivers) from the neutral mutations (passengers). This is a very timeconsuming task where a clinical pathologist has to manually review and classify every single genetic mutation based on evidence from text-based clinical literature. We need your help to develop a Machine Learning algorithm that, using this knowledge base as a baseline, automatically classifies genetic variations. The main challenge for crowdsourcing efforts is the required large, well-labeled public or semipublic datasets in order to get the proper community involvement. Nobody could have predicted the benefits that derived from the careful creation of the ImageNet database [99], and we conjecture that the expanded creation of similar high-quality databases for health data could also lead to unforeseen advances. There are already websites that are perfectly positioned to host such competitions, such as Kaggle [94]. A second major challenge to online competitions is in how to move competition-resulting software to clinical tools. One unique feature of this competition over some of the data-analysis-only competitions is that it will require creating teams of data scientists, software engineers, designers, and clinicians working together. A third major challenge is that competitions, thus far, are mostly limited to image recognition/computer vision. Complex and heterogeneous datasets, noisy medical datasets are not yet addressed (see Section 6. Yet, in contrast, large data-gathering projects (like the All of Us Research Program, see Section 5. Data fusion, the integration of multiple heterogeneous data sources, is an example suggestion for a new type of contest. Health data has features that make it unique from all other types of data, and contests could be designed to facilitate an understanding of what those features are, and how to correct for them. One example could be giving participants access to both electronic health records and billing data for a collection of patients that would require creative data linkage strategies to develop matched data and corresponding analyses. Citizen Science is a form of collaboration where members of the public participate in scientific research, a paradigm where the activities of an engaged public are intertwined with professional scientific research. One recent medical-related citizen science example is on bacterial resistance to antibiotics [102]. Understanding which changes in 31 the bacterial genome (mutations) lead to antibiotic resistance enables the identification of which antibiotics can be used to treat a particular patient, in a week rather than current practice of a month. Each sample will have its genome sequenced and for each sample the volunteers will help determine the sample’s sensitivity to a range of antibiotics based on images of plates with different antibiotic doses where bacteria have been allowed to grow. Volunteers are simply asked to view images of plates and identify whether or not bacteria are growing. Here the hosts aim to compare and combine inputs by the volunteers, expert opinion, and computer processing of images to get an accurate assessment of each plate. Public forums are needed to engage citizen scientists in helping find new discoveries that will benefit health and wellness. The creation of discovery-based challenges that build on crowdsourcing and citizen science lessons learned from other areas of science and engineering. However, various techniques are in fact known for utilizing deep learning in contexts where labeled data are unavailable or impractical. Three worth mentioning are reinforcement learning, auto-encoders, and generative adversarial networks. In reinforcement learning, typically, the input to a deep neural net is a complex image or feature set, while the output is supposed to be a set of policies that maximize a score. To train the net, we must provide an algorithm that evaluates and scores the output policies. In an early successful example, the input images were the continuous screenshots of the Atari game Pong, while the output policies were joystick moves that the computer makes. The score in this case is simply the Atari score displayed on the screen (which, in effect, the computer learns to read). So, in this example, as a substitute for labeled data, the computer simply plays the game many millions of times. Auto-encoders provide a methodology for autonomously learning to summarize a complex input signal (an image, for example) in terms of a small(er) number of features. The decoder side starts with these features and attempts to re-synthesize the original complex input. The auto-encode is trained using (as before) a lot of unlabeled – real or simulated – images. The training goal is to maximize the fidelity of the output image, as compared to the input image, after passing through the narrow neck of the feature vector. Once it is trained, we can use the auto-encoder in real time in two ways: It can produce feature vector output from complex input. As a notional example in health care, we might use an auto-encoder to learn how to do differential diagnosis, where the small number of features at the narrow neck are the diagnoses, while the complex input (and synthesized output) are the continuous signals of heart monitors, etc. In generative adversarial networks (or other similar adversarial networks) we allow two deep neural nets to play against each other, so that each becomes good at countering the behavior of the other. In a symmetric example, the two networks could be players in a two-person game. Playing against itself (actually an independent copy of itself), the network learns to become a good Go player. In asymmetric examples, one network is often termed generative, the other discriminative. The job of the generative network is to generate images (say) that fool the discriminative network, while the job of the discriminative network is not to be fooled.

Some of these comments could be minor (such as typos) or major (such as further analyses) depression symptoms guilt buy amitriptyline toronto. The next step for the authors is to address each and every comment received with as much details as possible depression organizations cheap amitriptyline 25mg overnight delivery, by either abiding by the suggestions or by not taking them into consideration depression definition in economy purchase amitriptyline 50mg. At this point mood disorder due to medical condition buy 25mg amitriptyline amex, the modified draft of the manuscript anxiety essential oils best purchase for amitriptyline, along with a point by point letter addressing the comments should be sent to the journal depression fatigue 25 mg amitriptyline with visa, through the online system. Rejection Rejection which indicates that the manuscript is rejected for publication in that journal, for reasons that might be based on the topic, the quality, the conclusion, or just that it does not fall within the scope of the journal. At this point, the authors should look for another journal to which they should submit their manuscript. Although the publication process might be time and effort consuming, it is very important and it gets easier with time, as the researcher publishes more papers. One last thing to keep in mind is that most research projects are publishable in scientific journals, but the type and impact of the journal in which it will be published might differ. By patient values we mean the specific preferences, concerns, personal values, and expectations of each patient. Currently this approach is inadequate and poor as health care workers rapidly find themselves unable to cope with the influx of a huge variety of new information, from the irrelevant to the very important. Our daily need for valid information about diagnosis, prognosis, therapy and prevention. The inadequacy of traditional sources for this information because they might be out-of-date (textbooks), potentially wrong (colleagues), or too overwhelming in their volume (medical journals). The disparity between our diagnostic skills/clinical judgment, which increases with experience, and our up-to-date knowledge which declines with time. Our inability to afford more than a few minutes per patient for finding and assimilating this evidence or to set aside more than few hours per week for general reading and study. Evidence alone is never the sole basis for decisions: Benefits and risks, costs and alternative strategies, as well as the patients‟ values are all factors that must be taken into consideration alongside with evidence when taking the decision. Thus, the physician must begin with the highest available evidence from the hierarchy. Ex: Young children with otitis media  I: the Intervention or exposure being considered. The overall question becomes: Does Amoxicillin lead to faster improvement in otitis media among young children compared to placebo? Acquiring the Evidence: In this step we make a systematic retrieval of the best evidence available. Appraisal of evidence: It is the process of assessing and evaluating the evidence for its internal validity, its clinical relevance, and applicability. Application of the best evidence in practice: Based on the findings of the above, a clinical decision is to be made. Assessing and evaluating the performance: Evaluating our effectiveness and efficiency in executing Steps 1 4 and seeking ways to improve them both for next time. Lag in time between when the research studies is conducted, when its results are published when these are properly applied 6. More specifically, research knowledge includes understanding of research process, ethical consideration, study design, statistical analyses, and results interpretation. Formulating a researchable question: A critical step for facilitating good clinical research. Practical tips for surgical research: Research questions, hypotheses and objectives. A Systems Approach to Conduct an Effective Literature Review in Support of Information Systems Research. Practical Strategies and Guidelines for Conducting Literature Reviews in Research. A 15-step model for writing a research proposal British Journal of Midwifery, 2010. Writing a Research Proposal: A guide for Science and Engineering students 2013; Available from: services. The importance of Good Clinical Practice guidelines and its role in clinical trials. Ethical and legal issues in research involving human subjects: do you want a piece of me? Data Analysis and Presentation Skills: An Introduction for the Life and Medical Sciences. Prevalence, Awareness, Treatment, and Control of Hypertension among Saudi Adult Population: A National Survey. Maternal and neonatal risk factors for early-onset group B streptococcal disease: a case control study. Efficiency of case-control studies with multiple controls per case: continuous or dichotomous data. Body mass index and obstetric outcomes in pregnant in Saudi Arabia: a prospective cohort study. Neonatal short-term outcomes of gestational diabetes mellitus in saudi mothers: a retrospective cohort study. Intensive versus conventional insulin therapy: a randomized controlled trial in medical and surgical critically ill patients. Uniform requirements for manuscripts submitted to biomedical journals: Writing and editing for biomedical publication. Title of Proposal: (Instructions: Fill all appropriate boxes apply to your project) 2. Type of Project: (please check all applicable options) Chart Review Diagnostic Qualitative Research Quantitative Research Human Laboratory Therapeutic Basic Science Other 3. Advisor‟s Name & Signature: Date: 79 Appendices 8. Abstract: (up to 200 words): Concisely describe the aims of study, methodology, short and long-term objective and the significance of the study to health problems in Saudi Arabia. Specific aim(s): (up to one page) 81 Appendices 10. Background and significance: (1 to 3pages) (Instructions: Literature review of previous studies on the subject; and justification of the study by stating the problem and its importance). This description will cover the details relevant to the study topic) 11. Literature cited: (Instructions: List the references cited in the sequence they appear in the proposal, and used Vancouver style) 88 Appendices 14. Gap in knowledge Conclude the Introduction section with a statement about the objective(s) of the study Methods Study design: Setting: Study population: 1. Multivariate Results Overall description of participants (demographic characteristics and socioeconomic profile) Summary of findings Multivariate analyses Discussion Summary of study and findings 1. Medications and clinical services are integral to the myriad roles pharmacists play in the healthcare system. Pharmaceutical research and development is instrumental in the discovery of new medications and pharmaceutical formulations. There are more than 10,000 prescription products and more than 300,000 over-the-counter products in the marketplace. During the past few decades, there has been signifcant growth of clinical pharmacy services to meet the complexities of delivering pharmaceutical care in diverse healthcare settings. Pharmacists provide a broad range of outpatient services, such as medication therapy management, immunizations, and health screenings, and inpatient services ranging from nutrition to therapeutic drug monitoring in institutional settings. High-quality research is vital to developing new medications and clinical services; it also provides the knowledge base to efectively use these products and services. Pharmacists have an important role to play in creating and applying scientifc evidence. Although pharmacists are mostly consumers of research information, they contribute immensely to the growing scientifc knowledge base relevant to the pharmacy profession. Pharmacists involved in research make a vital diference by providing evidence that others can use. This knowledge is also important in academia to train the next generation of pharmacists. In recent years, practice-based innovations have created new models in delivering pharmaceutical care. With the increasing role of evidencebased paradigms, there is greater need to critically apply and evaluate research for pharmaceutical practice and policy. Both creating and applying research evidence require an understanding of the principles of research design. This chapter defnes biomedical research and evolving clinical research paradigms relevant to the pharmacy practice. It discusses the principles of research design and steps involved in scientifc research inquiry. Finally, the concept of evidence-based medicine is introduced to efectively translate scientifc evidence to patient care. Research drives the increasing role of pharmaceuticals and pharmaceutical services in disease state management. Biomedical research can be further classifed as basic or applied based on the goals of the research. Basic research is defned as systematic study directed toward fuller knowledge or understanding of the fundamental aspects of phenomena and of observable facts without specifc applications toward processes or products in mind. Some areas of inquiry in basic biomedical research are biology, physiology, biochemistry, and genetics. Although scientists involved in basic research are only focused on generalized knowledge, this knowledge is critical for applied research that is product or application oriented. It has practical orientation rather than the explanation focus that is inherent in basic research. It is conducted in animals and other living systems to solve a practical problem or to create a product. Some areas of inquiry in applied biomedical research are pharmacology, medicinal chemistry, and pharmaceutics. Research and development in applied biomedical research is the engine for the pharmaceutical industry. Development is defned as systematic application of knowledge or understanding, directed toward the production of useful materials, devices, and systems or methods. It takes an average of 15 years for a new product to enter the market at an average cost of $1. It is conducted in laboratories, healthcare settings, and other specialized locations according to regulatory guidelines. Clinical research includes patient-oriented research, epidemiological and behavioral research, and health services research. Epidemiological and behavioral research evaluates the distribution of and factors associated with diseases, health behavior, and health in general. Health services research evaluates the efectiveness and efciency of treatment, interventions, and services in real-world practice. Clinical research involving pharmaceuticals and pharmacy services is vital to improving the quality of pharmaceutical care. Pharmaceutical practice and policy research is a component of health services research that deals with issues related to pharmaceuticals, pharmacist services, and pharmacy systems. It is defned as a multidisciplinary feld of scientifc investigation that examines cost, access, and quality of pharmaceutical care from clinical, sociobehavioral, economic, organizational, and technological perspectives. New areas such as pharmacoepidemiology, pharmacoeconomics, pharmaceutical outcome research, and pharmacy practice-based research are evolving and expanding the research Evolving Research Paradigms 5 frontiers of pharmaceutical practice and policy research. This evidence base is critical to expanding the scope and role of pharmacists and pharmacy systems. The second area of translation concerns research aimed at enhancing the adoption of best practices in the community. The second area of translation is gaining the support of scientists, clinicians, educators, and funding agencies to rapidly adopt evidence-based patient care practices. In recent years, there is signifcant interest in comparative efectiveness research due to limited data comparing two therapies, interventions, or devices. The demand for comparative efectiveness data is apparent as most clinicians want such data for clinical decisions. The efcacy data derived from placebo-controlled clinical trials are designed for the drug approval process. Comparative efectiveness research is based on the concepts of evaluation of alternatives so that the research can be used to select appropriate agents from among the alternatives to optimize patient outcomes. Comparative efectiveness research is the generation and synthesis of evidence that compares the benefts and harms of alternative methods to prevent, diagnose, treat, and monitor a clinical condition or to improve delivery of care. It is based on the philosophy of positivism that states that all information derived from sensory experience is empirical evidence of science. All aspects of science should be observed and measured to be considered scientifc evidence. All clinical outcomes in research are explicitly defned and measured to be considered evidence to evaluate the safety and efectiveness of medications. Objectivity means there is no subjectivity or bias in any aspect of research including defnition, measurement, design, and analysis. In clinical research, the measures to defne efectiveness, such as blood pressure and blood glucose, are objective, and the measurement process is ofen blinded to minimize any kind of subjectivity. All biases in research are minimized to increase the strength of scientifc evidence. In pharmaceutical research, theories are ofen based on the pathophysiology of a disease and the pharmacology of a medication to investigate its efects. Sociobehavioral theories are ofen used to understand patient and provider behavior in pharmaceutical practice and policy research. These standards are based on respect for, fairness to , and the wellbeing of research participants. To refect all these principles in research, Kerlinger has defned scientifc research as a systematic, controlled, empirical, and critical investigation guided by theory and hypothesis about presumed relationships among such phenomena.

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