Comparison of Conventional Logistic Regression and Machine Learning Methods for Predicting Delayed Cerebral Ischemia After Aneurysmal Subarachnoid Hemorrhage: A Multicentric Observational Cohort Study

BACKGROUND: Timely and accurate prediction of delayed cerebral ischemia is critical for improving the prognosis of patients with aneurysmal subarachnoid hemorrhage. Machine learning (ML) algorithms are increasingly regarded as having a higher prediction power than conventional logistic regression (L...

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Detalles Bibliográficos
Autores principales: Hu, Ping, Li, Yuntao, Liu, Yangfan, Guo, Geng, Gao, Xu, Su, Zhongzhou, Wang, Long, Deng, Gang, Yang, Shuang, Qi, Yangzhi, Xu, Yang, Ye, Liguo, Sun, Qian, Nie, Xiaohu, Sun, Yanqi, Li, Mingchang, Zhang, Hongbo, Chen, Qianxue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Aging Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9247265/
https://www.ncbi.nlm.nih.gov/pubmed/35783143
http://dx.doi.org/10.3389/fnagi.2022.857521

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9247265/
https://www.ncbi.nlm.nih.gov/pubmed/35783143
http://dx.doi.org/10.3389/fnagi.2022.857521

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