Articles liés à Data-Driven Approaches for Health Care: Machine Learning...
Data-Driven Approaches for Health Care: Machine Learning for Identifying High Utilizers - Couverture rigide
Synopsis
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:
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l?auteur
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, Department of Computer Science, University of Florida.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Acheter neuf
Afficher cet article
EUR 175,44
EUR 10,99 expédition depuis Royaume-Uni vers France
Destinations, frais et délais
Résultats de recherche pour Data-Driven Approaches for Health Care: Machine Learning...
Image d'archives
Data Driven Approaches for Healthcare : Machine learning for Identifying High Utilizers
Edité par
Taylor & Francis Ltd, 2019
ISBN 10 : 0367342901
ISBN 13 : 9780367342906
Ancien ou d'occasion
Couverture rigide
Vendeur : Buchpark, Trebbin, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Etat : Sehr gut. Zustand: Sehr gut | Seiten: 108 | Sprache: Englisch | Produktart: Bücher. N° de réf. du vendeur 35591977/2
Quantité disponible : 1 disponible(s)
Image d'archives
Data Driven Approaches for Healthcare: Machine learning Approaches for Identifying High Utilizers (Chapman & Hall/CRC Big Data Series)
Edité par
Chapman and Hall/CRC 2019-10-10, 2019
ISBN 10 : 0367342901
ISBN 13 : 9780367342906
Neuf
Couverture rigide
Vendeur : Chiron Media, Wallingford, Royaume-Uni
Évaluation du vendeur 4 sur 5 étoiles
Hardcover. Etat : New. N° de réf. du vendeur 6666-TNF-9780367342906
Quantité disponible : 10 disponible(s)
Image fournie par le vendeur
Yang, C: Data Driven Approaches for Healthcare
impression à la demandeVendeur : moluna, Greven, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Etat : 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. N° de réf. du vendeur 594574941
Quantité disponible : Plus de 20 disponibles
Image d'archives
Data Driven Approaches for Healthcare: Machine learning for Identifying High Utilizers (Chapman & Hall/CRC Big Data Series)
Edité par
Chapman and Hall/CRC, 2019
ISBN 10 : 0367342901
ISBN 13 : 9780367342906
Neuf
Couverture rigide
Vendeur : Majestic Books, Hounslow, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. N° de réf. du vendeur 390536978
Quantité disponible : 3 disponible(s)
Image d'archives
Data Driven Approaches for Healthcare: Machine learning for Identifying High Utilizers (Chapman & Hall/CRC Big Data Series)
Edité par
Chapman and Hall/CRC, 2019
ISBN 10 : 0367342901
ISBN 13 : 9780367342906
Neuf
Couverture rigide
Vendeur : Books Puddle, New York, NY, Etats-Unis
Évaluation du vendeur 4 sur 5 étoiles
Etat : New. 1st edition NO-PA16APR2015-KAP. N° de réf. du vendeur 26389062861
Quantité disponible : 3 disponible(s)
Image d'archives
Data-Driven Approaches for Health Care: Machine Learning for Identifying High Utilizers
Vendeur : Revaluation Books, Exeter, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Hardcover. Etat : Brand New. 107 pages. 10.00x7.25x0.50 inches. In Stock. N° de réf. du vendeur __0367342901
Quantité disponible : 1 disponible(s)
Image d'archives
Data Driven Approaches for Healthcare: Machine learning for Identifying High Utilizers (Chapman & Hall/CRC Big Data Series)
Edité par
Chapman and Hall/CRC, 2019
ISBN 10 : 0367342901
ISBN 13 : 9780367342906
Neuf
Couverture rigide
Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. N° de réf. du vendeur 18389062855
Quantité disponible : 3 disponible(s)
Image d'archives
Data Driven Approaches for Healthcare: Machine learning for Identifying High Utilizers
Edité par
Taylor & Francis Ltd, 2019
ISBN 10 : 0367342901
ISBN 13 : 9780367342906
Neuf
Couverture rigide
Vendeur : THE SAINT BOOKSTORE, Southport, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Hardback. Etat : New. New copy - Usually dispatched within 4 working days. 419. N° de réf. du vendeur B9780367342906
Quantité disponible : 1 disponible(s)
Image d'archives
Data Driven Approaches for Healthcare (Hardcover)
Edité par
Taylor & Francis Ltd, London, 2019
ISBN 10 : 0367342901
ISBN 13 : 9780367342906
Neuf
Couverture rigide
Vendeur : Grand Eagle Retail, Mason, OH, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
Hardcover. Etat : 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. N° de réf. du vendeur 9780367342906
Quantité disponible : 1 disponible(s)
Image d'archives
Data Driven Approaches for Healthcare (Hardcover)
Edité par
Taylor & Francis Ltd, London, 2019
ISBN 10 : 0367342901
ISBN 13 : 9780367342906
Neuf
Couverture rigide
Vendeur : AussieBookSeller, Truganina, VIC, Australie
Évaluation du vendeur 5 sur 5 étoiles
Hardcover. Etat : 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. N° de réf. du vendeur 9780367342906
Quantité disponible : 1 disponible(s)