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Fundamentals of Clinical Data Science [electronic resource]
Kubben, Pieter
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| 자료유형 | 단행본 |
|---|---|
| 개인저자 | Kubben, Pieter.,editor. Dumontier, Michel.,editor. Dekker, Andre.,editor. |
| 단체저자명 | SpringerLink (Online service). |
| 서명/저자사항 | Fundamentals of Clinical Data Science [electronic resource] / edited by Pieter Kubben, Michel Dumontier, Andre Dekker. |
| 판사항 | 1st ed. 2019. |
| 형태사항 | VIII, 219 p. 45 illus., 35 illus. in color:online resource. |
| 기본자료 저록 | Springer Nature eBook |
| 기타형태 저록 | Printed edition:9783319997124Printed edition:9783319997148 |
| ISBN | 9783319997131 |
| 기타표준부호 | 10.1007/978-3-319-99713-1 |
| 내용주기 | Data sources -- Data at scale -- Standards in healthcare data -- Using FAIR data / data stewardship -- Privacy / deidentification -- Preparing your data -- Creating a predictive model -- Diving deeper into models -- Validation and Evaluation of reported models -- Clinical decision support systems -- Mobile app development -- Operational excellence -- Value Based Healthcare (Regulatory concerns). |
| 이용제한사항 | Open Access |
| 요약 | 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. |
| 일반주제명 | Medical informatics. Bioinformatics. Health Informatics. Computational and Systems Biology. |
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