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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

Current clinical diagnostic models lack sufficient sensitivity and specificity for Hepatoblastoma (HB) individualized prediction. This study aimed to identify robust hub genes for HB diagnosis and molecular subtyping by integrating multiple transcriptomic datasets and machine learning algorithms. Four merg...

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

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