Anbieter: SpringBooks, Berlin, Deutschland
Erstausgabe
Hardcover. Zustand: Very Good. 1. Auflage. Unread, with some shelfwear. Immediately dispatched from Germany.
EUR 53,03
Anzahl: 2 verfügbar
In den WarenkorbHardcover. Zustand: Brand New. 219 pages. 9.25x6.25x0.75 inches. In Stock.
Zustand: new.
Sprache: Englisch
Verlag: Springer International Publishing Jan 2019, 2019
ISBN 10: 3319997122 ISBN 13: 9783319997124
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Buch. Zustand: Neu. Neuware -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.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 232 pp. Englisch.
Sprache: Englisch
Verlag: Springer International Publishing, 2019
ISBN 10: 3319997122 ISBN 13: 9783319997124
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 Scienceis 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.