Discovering patient groups in sequential electronic healthcare data using unsupervised representation learning.
Journal:
BMC medical informatics and decision making
PMID:
39875929
Abstract
INTRODUCTION: Unsupervised feature learning methods inspired by natural language processing (NLP) models are capable of constructing patient-specific features from longitudinal Electronic Health Records (EHR).