Fundamentals of Clinical Data Science [electronic resource]

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Tác giả: Andre Dekker, Michel Dumontier, Pieter Kubben

Ngôn ngữ: ger

ISBN-13: 978-3319997131

Ký hiệu phân loại: 502.85 Miscellany

Thông tin xuất bản: Cham : Springer International Publishing : Imprint: Springer, 2019

Mô tả vật lý: VIII, 219 p. 45 illus., 35 illus. in color. , online resource.

Bộ sưu tập: Tài liệu truy cập mở

ID: 169222

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.
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