Neural network-based clustering model of ischemic stroke patients with a maximally distinct distribution of 1-year vascular outcomes.

ABSTRACT: Clustering stroke patients with similar characteristics to predict subsequent vascular outcome events is critical. This study aimed to compare several clustering methods, particularly a deep neural network-based model, and identify the best clustering method with a maximally distinct 1-year outcome in patients with ischemic stroke. Prospective stroke registry data from a comprehensive stroke center from January 2011 to July 2018 were retrospectively analyzed. Patients with acute ischemic stroke within 7 days of onset were included. The primary outcomes were the composite of all strokes (either hemorrhagic or ischemic), myocardial infarction, and all-cause mortality within one year. Neural network-based clustering models (deep lifetime clustering) were compared with other clustering models

SUBMITTER: Kim JT 

PROVIDER: S-EPMC9177616 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature