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Using Machine Learning to Improve Personalised Prediction: A Data-Driven Approach to Segment and Stratify Populations for Healthcare.

Authors :
YUILL, Will
KUNZ, Holger
Source :
Studies in Health Technology & Informatics; 2022, Vol. 289, p29-32, 4p, 1 Diagram, 1 Chart
Publication Year :
2022

Abstract

Population Health Management typically relies on subjective decisions to segment and stratify populations. This study combines unsupervised clustering for segmentation and supervised classification, personalised to clusters, for stratification. An increase in cluster homogeneity, sensitivity and positive predictive value was observed compared to an unlinked approach. This analysis demonstrates the potential for a cluster-then-predict methodology to improve and personalise decisions in healthcare systems. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09269630
Volume :
289
Database :
Complementary Index
Journal :
Studies in Health Technology & Informatics
Publication Type :
Academic Journal
Accession number :
155372554
Full Text :
https://doi.org/10.3233/SHTI210851