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Public Health Tools to Control Diabetes Care: Advanced Data Analysis. Situation, problems, solutions and evaluation using clinical real data samples
В наличии
Местонахождение: Алматы | Состояние экземпляра: новый |
Бумажная
версия
версия
Автор: Simion Pruna
ISBN: 9783847340317
Год издания: 2014
Формат книги: 60×90/16 (145×215 мм)
Количество страниц: 368
Издательство: LAP LAMBERT Academic Publishing
Цена: 64456 тг
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Позиции в рубрикаторе
Отрасли знаний:Код товара: 112671
Способы доставки в город Алматы * комплектация (срок до отгрузки) не более 2 рабочих дней |
Самовывоз из города Алматы (пункты самовывоза партнёра CDEK) |
Курьерская доставка CDEK из города Москва |
Доставка Почтой России из города Москва |
Аннотация: Electronically collected medical data at point of care in daily management of diabetic patients, access to datasets and advanced data analysis can identify patients with diabetes at high risk for chronic complications. They offer a guide for appropriate evidence based health care practice. The observational studies presented here offer health information on clinical and laboratory parameters related to diabetic patients. Patients can make their disease life much easier by getting to know specialist vocabulary presented in a brief introduction about ‘data understanding’ of each health parameter analysed. Therefore, the findings of data analysis will guide the patients to achieve immediate impact on disease control. Medical professionals, health services managers and health policy-makers can benefit from the technology presented here (advanced data analysis and electronic registries) to derive actionable information triggering health care interventions to enhance quality in health care. Health research scientists and authors of dissertations can utilise the numerous screenshots, tables and charts presented in this book to save time and efforts in their research.
Ключевые слова: Diabetes, advanced data analysis, data understanding, outcome indicators, diabetes complications, obesity and diabetes, hypertension in diabetes, challenges in data analysis, Medical Informatics, EHR, clinical diabetes registry