Predicting new-onset post-stroke depression from real-world data using machine learning algorithm

Predicting new-onset post-stroke depression from real-world data using machine learning algorithm

IntroductionPost-stroke depression (PSD) is a serious mental disorder after ischemic stroke. Early detection is important for clinical practice. This research aims to develop machine learning models to predict new-onset PSD using real-world data.MethodsWe collected data for ischemic stroke patients...

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Bibliographic Details
Main Authors: Yu-Ming Chen, Po-Cheng Chen, Wei-Che Lin, Kuo-Chuan Hung, Yang-Chieh Brian Chen, Chi-Fa Hung, Liang-Jen Wang, Ching-Nung Wu, Chih-Wei Hsu, Hung-Yu Kao
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-06-01
Series:Frontiers in Psychiatry
Subjects:
artificial intelligence
depressive disorder
electronic medical record
feature importance
prediction
Online Access:https://www.frontiersin.org/articles/10.3389/fpsyt.2023.1195586/full

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https://www.frontiersin.org/articles/10.3389/fpsyt.2023.1195586/full

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