Da: California Books, Miami, FL, U.S.A.
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Da: Ria Christie Collections, Uxbridge, Regno Unito
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Da: Biblios, Frankfurt am main, HESSE, Germania
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Da: Chiron Media, Wallingford, Regno Unito
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Aggiungi al carrelloPaperback. Condizione: New.
Condizione: New.
Lingua: Inglese
Editore: Taylor & Francis Ltd, London, 2019
ISBN 10: 0367342901 ISBN 13: 9780367342906
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Hardcover. Condizione: 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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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 208,97
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Da: Majestic Books, Hounslow, Regno Unito
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Da: Buchpark, Trebbin, Germania
EUR 135,63
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Da: Revaluation Books, Exeter, Regno Unito
EUR 237,17
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Aggiungi al carrelloHardcover. Condizione: Brand New. 107 pages. 10.00x7.25x0.50 inches. In Stock.
Da: moluna, Greven, Germania
EUR 200,28
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Aggiungi al carrelloCondizione: 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.
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 248,74
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Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 244,94
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Aggiungi al carrelloCondizione: New.
Lingua: Inglese
Editore: Taylor & Francis Ltd Okt 2019, 2019
ISBN 10: 0367342901 ISBN 13: 9780367342906
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 245,50
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Aggiungi al carrelloBuch. Condizione: Neu. Neuware.
Lingua: Inglese
Editore: Taylor & Francis Ltd, London, 2019
ISBN 10: 0367342901 ISBN 13: 9780367342906
Da: AussieBookSeller, Truganina, VIC, Australia
EUR 300,56
Quantità: 1 disponibili
Aggiungi al carrelloHardcover. Condizione: 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.
Da: PBShop.store US, Wood Dale, IL, U.S.A.
EUR 78,09
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Aggiungi al carrelloPAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
EUR 74,46
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Aggiungi al carrelloPAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Da: moluna, Greven, Germania
EUR 55,75
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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.
Da: preigu, Osnabrück, Germania
EUR 78,30
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Data Driven Approaches for Healthcare | Machine learning for Identifying High Utilizers | Chengliang Yang (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2021 | Chapman and Hall/CRC | EAN 9781032088686 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 91,94
Quantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.