Data Driven Approaches for Healthcare - Machine Learning for Identifying High Utilizers

Sommario

Introduction. Overview of Healthcare Data. Machine Learning Modeling from Healthcare Data. Machine Learning Modeling from Healthcare Data. Descriptive Analysis of High Utlizers. Residuals Analysis for Identifying High Utilizers.Machine Learning Results for High Utilizers.

Info autore

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.

Riassunto

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.

Dettagli sul prodotto

• Autori: Chris Delcher, Chris (University of Kentucky Delcher, Sanjay Ranka, Sanjay (University of Florida Ranka, Ranka Sanjay, Elizabeth Shenkman, Elizabeth (University of Florida Shenkman, Chengliang Yang, Chengliang Delcher Yang
• Editore: Taylor & Francis Ltd.
• Lingue: Inglese
• Formato: Copertina rigida
• Pubblicazione: 31.10.2019
• EAN: 9780367342906
• ISBN: 978-0-367-34290-6
• Pagine: 118
• Serie: Chapman & Hall/CRC Big Data Series
• Categorie: Scienze naturali, medicina, informatica, tecnica > Medicina > Tematiche generali; SELF-HELP / General, HEALTH & FITNESS / General, COMPUTERS / Computer Science, MEDICAL / Health Care Delivery, TECHNOLOGY & ENGINEERING / Automation, COMPUTERS / Networking / General, COMPUTERS / System Administration / General, TECHNOLOGY & ENGINEERING / Industrial Health & Safety, computer science, Health & personal development, Health & safety aspects of IT, Information technology: general issues, Automatic control engineering, Databases, Health, Relationships and Personal development, Health systems & services, Information technology: general topics, Health systems and services, COMPUTERS / Social Aspects, Network Management, COMPUTERS / Database Administration & Management, Digital and Information technology: general topics