Predicting functional outcomes of patients with spontaneous intracerebral hemorrhage based on explainable machine learning models: a multicenter retrospective study

BackgroundSpontaneous intracerebral hemorrhage (SICH) is the second most common cause of cerebrovascular disease after ischemic stroke, with high mortality and disability rates, imposing a significant economic burden on families and society. This retrospective study aimed to develop and evaluate an...

ver descrição completa

Detalhes bibliográficos

Principais autores:	Bin Pan, Fengda Li, Chuanghong Liu, Zeyi Li, Chengfa Sun, Kaijian Xia, Hong Xu, Gang Kong, Longyuan Gu, Kaiyuan Cheng
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Frontiers Media S.A. 2025-01-01
Colecção:	Frontiers in Neurology
Assuntos:	spontaneous intracerebral hemorrhage machine learning prognostic prediction XGBoost SHAP
Acesso em linha:	https://www.frontiersin.org/articles/10.3389/fneur.2024.1494934/full
Tags:	Adicionar Tag Sem tags, seja o primeiro a adicionar uma tag!