Interpretable machine learning for cognitive impairment assessment: integration of clinical and radiomic white matter hyperintensities features

Abstract Background White matter hyperintensities (WMH) are recognized as important imaging biomarkers associated with cognitive impairment. This study aimed to develop a machine learning model that combines clinical data and WMH radiomic features for improving the assessment of cognitive impairment...

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Hlavní autoři:	Mengchen Wang, Tianci Wang, Xiaoxiao Wang, Chun Liu, Frankliu Gao, Bensheng Qiu, Tao Guo, Yu Huang
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	BMC 2026-02-01
Edice:	Journal of Translational Medicine
Témata:	White matter hyperintensities Radiomics Clinical data Machine learning Cognitive impairment
On-line přístup:	https://doi.org/10.1186/s12967-026-07843-6
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