| 書目名稱 | Fundamentals of Clinical Data Science | | 編輯 | Pieter Kubben,Michel Dumontier,Andre Dekker | | 視頻video | http://file.papertrans.cn/351/350179/350179.mp4 | | 概述 | Provides a resource for healthcare professionals on smart algorithms.Integrates the data, modelling, clinical application levels of clinical data science.Focuses on relevant non math and code aspects | | 圖書封面 |  | | 描述 | .This open access book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications.? Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and? related privacy concerns. Aspects of? predictive modelling? using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare...Fundamentals of Clinical Data Science?.is an essential resource for healthcare professionals and IT consultants intending to develop and refine their skills in personalized medicine, using solutions based on large datasets from electronic health records or telemonitoring programmes. The book’s promise is .“no math, no code”.and will explain the topics in a style that is optimized for a healthcare audience.. | | 出版日期 | Book‘‘‘‘‘‘‘‘ 2019 | | 關(guān)鍵詞 | eHealth; mHealth; Predictive analytics; Machine learning; Personalized medicine; Value based healthcare; B | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-319-99713-1 | | isbn_ebook | 978-3-319-99713-1 | | copyright | The Editor(s) (if applicable) and The Author(s) 2019 |
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