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Open access Sep 2026

Interpretable machine learning for postoperative sepsis prediction in ICU patients following intracranial hematoma evacuation

Background Sepsis is a prevalent and life-threatening complication in ICU patients after intracranial hematoma evacuation. This study aimed to develop and externally validate an interpretable machine learning model for predicting sepsis risk in this high-risk neurocritical care population. Methods A multicenter retrosp...

Shao-Yang Yu, Yun Liu, Lei Guo et al. · 0 citations
Open access Sep 2026

Integrated machine learning and multi-dataset analysis identify SDS as a diagnostic and immune-related hub gene in hepatoblastoma

Integrated machine learning identified CLEC1B, ITGA6, SDS, and TTC36 as robust diagnostic genes for hepatoblastoma and SDS exerts a tumor-suppressive role and is closely linked to the immune microenvironment, making it a promising diagnostic biomarker and therapeutic target in HB.

Dan Chen, Bai-Xue Zhang, Yan-Long Zhang et al. · 0 citations

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