Multimorbidity in middle-aged women and COVID-19: binary data clustering for unsupervised binning of rare multimorbidity features and predictive modeling

Abstract Background Multimorbidity is typically associated with deficient health-related quality of life in mid-life, and the likelihood of developing multimorbidity in women is elevated. We address the issue of data sparsity in non-prevalent features by clustering the binary data of various rare me...

Full description

Bibliographic Details

Published in:	BMC Medical Research Methodology
Main Authors:	Dayana Benny, Mario Giacobini, Giuseppe Costa, Roberto Gnavi, Fulvio Ricceri
Format:	Article
Language:	English
Published:	BMC 2024-04-01
Subjects:	Clustering Sparse binary data Binary classification Multimorbidity Machine learning COVID-19
Online Access:	https://doi.org/10.1186/s12874-024-02200-x