Multi-feature fusion RFE random forest for schizophrenia classification and treatment response prediction

Multi-feature fusion RFE random forest for schizophrenia classification and treatment response prediction

Abstract Schizophrenia(SZ) classification and treatment response prediction hold substantial clinical application value. However, only a limited number of researchers have exploited the multi-feature information derived from resting-state functional magnetic resonance imaging (rs-fMRI) to achieve sh...

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Bibliographic Details
Main Authors: Chang Wang, Rui Zhang, Jiyuan Zhang, Yaning Ren, Ting Pang, Xiangyu Chen, Xiao Li, Zongya Zhao, Yongfeng Yang, Wenjie Ren, Yi Yu
Format: Article
Language:English
Published: Nature Portfolio 2025-03-01
Series:Scientific Reports
Subjects:
Schizophrenia classification
Treatment response prediction
Multi-feature Fusion
Recursive feature elimination
Random Forest
Online Access:https://doi.org/10.1038/s41598-025-89359-5
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https://doi.org/10.1038/s41598-025-89359-5

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