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9780367342906 - Data Driven Approaches for Healthcare: Machine Learning for Identifying High Utilizers Chapman & Hall/crc Big Data Series by Yang, Chengliang; Delcher, Chris; Shenk... (15 results)
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Data Driven Approaches for Healthcare : Machine Learning for Identifying High Utilizers
Book 10 of 13: Chapman & Hall/CRC Big Data SeriesSeller: Better World Books Ltd, Dunfermline, United Kingdom
Seller rating 5 out of 5 stars
Condition: Good. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.
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Data Driven Approaches for Healthcare : Machine learning for Identifying High Utilizers
Book 10 of 13: Chapman & Hall/CRC Big Data SeriesLanguage: English
Published by Taylor & Francis Ltd, 2019
ISBN 10: 0367342901 ISBN 13: 9780367342906
Condition: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.
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Data Driven Approaches for Healthcare (Hardcover)
Book 10 of 13: Chapman & Hall/CRC Big Data SeriesLanguage: English
Published by Taylor & Francis Ltd, London, 2019
ISBN 10: 0367342901 ISBN 13: 9780367342906
Hardcover. Condition: new. Hardcover. Health care utilization routinely generates vast amounts of data from sources ranging from electronic medical records, insurance claims, vital signs, and patient-reported outcomes. Predicting health outcomes using data modeling approaches is an emerging field that can reveal important insights into disproportionate spending patterns. This book presents data driven methods, especially machine learning, for understanding and approaching the high utilizers problem, using the example of a large public insurance program. It describes important goals for data driven approaches from different aspects of the high utilizer problem, and identifies challenges uniquely posed by this problem.Key Features:Introduces basic elements of health care data, especially for administrative claims data, including disease code, procedure codes, and drug codesProvides tailored supervised and unsupervised machine learning approaches for understanding and predicting the high utilizersPresents descriptive data driven methods for the high utilizer populationIdentifies a best-fitting linear and tree-based regression model to account for patients acute and chronic condition loads and demographic characteristics This book presents data driven methods, especially machine learning, for understanding and approaching the high utilizers problem, using the example of a large public insurance program. It describes important goals for data driven approaches from different aspects of the high utilizer problem, and identifies challenges posed by this problem. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Data-Driven Approaches for Health Care : Machine Learning for Identifying High Utilizers
Book 10 of 13: Chapman & Hall/CRC Big Data SeriesLanguage: English
Published by Chapman and Hall/CRC, 2019
ISBN 10: 0367342901 ISBN 13: 9780367342906
Condition: New.
-
Data-Driven Approaches for Health Care : Machine Learning for Identifying High Utilizers
Book 10 of 13: Chapman & Hall/CRC Big Data SeriesLanguage: English
Published by Chapman and Hall/CRC, 2019
ISBN 10: 0367342901 ISBN 13: 9780367342906
Condition: As New. Unread book in perfect condition.
-
Data-Driven Approaches for Health Care : Machine Learning for Identifying High Utilizers
Book 10 of 13: Chapman & Hall/CRC Big Data SeriesLanguage: English
Published by Chapman and Hall/CRC, 2019
ISBN 10: 0367342901 ISBN 13: 9780367342906
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Data Driven Approaches for Healthcare: Machine learning for Identifying High Utilizers (Chapman & Hall/CRC Big Data Series)
Book 10 of 13: Chapman & Hall/CRC Big Data SeriesLanguage: English
Published by Chapman and Hall/CRC, 2019
ISBN 10: 0367342901 ISBN 13: 9780367342906
Condition: New.
-
Data Driven Approaches for Healthcare: Machine learning for Identifying High Utilizers (Chapman & Hall/CRC Big Data Series)
Book 10 of 13: Chapman & Hall/CRC Big Data SeriesLanguage: English
Published by Chapman and Hall/CRC, 2019
ISBN 10: 0367342901 ISBN 13: 9780367342906
Condition: New. 1st edition NO-PA16APR2015-KAP.
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Hardcover. Condition: Brand New. 107 pages. 10.00x7.25x0.50 inches. In Stock.
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Data-Driven Approaches for Health Care : Machine Learning for Identifying High Utilizers
Book 10 of 13: Chapman & Hall/CRC Big Data SeriesLanguage: English
Published by Chapman and Hall/CRC, 2019
ISBN 10: 0367342901 ISBN 13: 9780367342906
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Gebunden. Condition: New. Chengliang Yang, Department of Computer Science, University of Florida Chris Delcher, Institute of Child Health Policy, University of Florida Elizabeth Shenkman, Institute of Child Health Policy, University of Florida Sanjay Ranka, Depar.
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Data Driven Approaches for Healthcare: Machine learning for Identifying High Utilizers (Chapman & Hall/CRC Big Data Series)
Book 10 of 13: Chapman & Hall/CRC Big Data SeriesLanguage: English
Published by Chapman and Hall/CRC, 2019
ISBN 10: 0367342901 ISBN 13: 9780367342906
Condition: New.
-
Data Driven Approaches for Healthcare: Machine learning for Identifying High Utilizers
Book 10 of 13: Chapman & Hall/CRC Big Data SeriesLanguage: English
Published by Taylor & Francis Ltd, 2019
ISBN 10: 0367342901 ISBN 13: 9780367342906
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
Hardback. Condition: New. New copy - Usually dispatched within 4 working days.
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Data Driven Approaches for Healthcare : Machine learning for Identifying High Utilizers
Book 10 of 13: Chapman & Hall/CRC Big Data SeriesLanguage: English
Published by Taylor & Francis Ltd Okt 2019, 2019
ISBN 10: 0367342901 ISBN 13: 9780367342906
Buch. Condition: Neu. Neuware.
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Data Driven Approaches for Healthcare (Hardcover)
Book 10 of 13: Chapman & Hall/CRC Big Data SeriesLanguage: English
Published by Taylor & Francis Ltd, London, 2019
ISBN 10: 0367342901 ISBN 13: 9780367342906
Hardcover. Condition: new. Hardcover. Health care utilization routinely generates vast amounts of data from sources ranging from electronic medical records, insurance claims, vital signs, and patient-reported outcomes. Predicting health outcomes using data modeling approaches is an emerging field that can reveal important insights into disproportionate spending patterns. This book presents data driven methods, especially machine learning, for understanding and approaching the high utilizers problem, using the example of a large public insurance program. It describes important goals for data driven approaches from different aspects of the high utilizer problem, and identifies challenges uniquely posed by this problem.Key Features:Introduces basic elements of health care data, especially for administrative claims data, including disease code, procedure codes, and drug codesProvides tailored supervised and unsupervised machine learning approaches for understanding and predicting the high utilizersPresents descriptive data driven methods for the high utilizer populationIdentifies a best-fitting linear and tree-based regression model to account for patients acute and chronic condition loads and demographic characteristics This book presents data driven methods, especially machine learning, for understanding and approaching the high utilizers problem, using the example of a large public insurance program. It describes important goals for data driven approaches from different aspects of the high utilizer problem, and identifies challenges posed by this problem. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
