Machine learning in developing a predictive model for chronic hydrocephalus following aneurysmal subarachnoid hemorrhage

ObjectiveUsing machine learning (ML) algorithms integrated with deep learning and radiomics technologies, we developed a nomogram model through an in-depth analysis and mining of clinical data and imaging features from patients with aneurysmal subarachnoid hemorrhage (aSAH). This model was aimed to...

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Auteurs principaux:	Rao Dai, Enxi Xu, Lixiang Zhang, Zehui Wang, Bowen Liu, Siyuan Lu, Xiuhong Shan, Eryi Sun
Format:	Artigo
Langue:	Inglês
Publié:	Frontiers Media S.A. 2026-01-01
Collection:	Frontiers in Neurology
Sujets:	clinical-radiological nomogram chronic hydrocephalus aneurysmal subarachnoid hemorrhage 3D-Unet machine learning
Accès en ligne:	https://www.frontiersin.org/articles/10.3389/fneur.2025.1651694/full
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