Articles liés à Fundamentals of Clinical Data Science
Synopsis
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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l?auteur
Pieter Kubben is a neurosurgeon, mobile app developer and programme manager for eHealth and mHealth for the Maastricht University Medical Center. Telemonitoring and corresponding algorithm development is a particular focus area Dr Kubben is involved in, as well as interactive clinical decision support systems.
Michel Dumontier is a distuinguished professor of data science at Maastricht University and head of the Institute for Data Science - connecting data science initiatives and projects from all faculties. He is also deeply involved in the FAIR data approach (Findable, Accessible, Interoperable, Reproducible).
André Dekker is a professor of clinical data science at Maastricht University and has been leading the development of prediction models in radiation therapy for many years. He is also coordinator of the Personal Health Train project, aiming to facilitate "citizen science".
.Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Fundamentals of Clinical Data Science [Hardcover] Kubben, Pieter; Dumontier, Michel and Dekker, Andre
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Springer, 2019
ISBN 10 : 3319997122
ISBN 13 : 9783319997124
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FUNDAMENTALS OF CLINICAL DATA SCIENCE
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Fundamentals of Clinical Data Science
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Fundamentals of Clinical Data Science
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ISBN 10 : 3319997122
ISBN 13 : 9783319997124
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Fundamentals of Clinical Data Science
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Fundamentals of Clinical Data Science
Edité par
Springer International Publishing, 2019
ISBN 10 : 3319997122
ISBN 13 : 9783319997124
Neuf
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Buch. Etat : 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. N° de réf. du vendeur 9783319997124
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Fundamentals of Clinical Data Science
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Springer International Publishing Jan 2019, 2019
ISBN 10 : 3319997122
ISBN 13 : 9783319997124
Neuf
Couverture rigide
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - 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 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. 232 pp. Englisch. N° de réf. du vendeur 9783319997124
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Fundamentals of Clinical Data Science
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Hardcover. Etat : Brand New. 219 pages. 9.25x6.25x0.75 inches. In Stock. N° de réf. du vendeur __3319997122
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Fundamentals of Clinical Data Science
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Fundamentals of Clinical Data Science
Edité par
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ISBN 10 : 3319997122
ISBN 13 : 9783319997124
Neuf
Couverture rigide
Vendeur : Rarewaves.com UK, London, Royaume-Uni
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Hardback. Etat : New. 1st ed. 2019. 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. N° de réf. du vendeur LU-9783319997124
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