Radiogenomic models using MRI features from multiple public datasets predicted the M0 macrophage immune signature in IDH-wildtype glioblastoma with mean balanced accuracy 0.67 and precision 0.89 on held-out cohorts.
Necroptosis-based glioblastoma prognostic subtypes: implications for TME remodeling and therapy response
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Machine learning models on a novel Romanian EHR dataset of 12,286 sepsis hospitalizations achieve AUC 0.983 for death versus recovery prediction and identify eosinopenia as a top predictor via SHAP.
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Predictive Radiomics for Evaluation of Cancer Immune SignaturE in Glioblastoma: the PRECISE-GBM study
Radiogenomic models using MRI features from multiple public datasets predicted the M0 macrophage immune signature in IDH-wildtype glioblastoma with mean balanced accuracy 0.67 and precision 0.89 on held-out cohorts.
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Explainable Machine Learning for Sepsis Outcome Prediction Using a Novel Romanian Electronic Health Record Dataset
Machine learning models on a novel Romanian EHR dataset of 12,286 sepsis hospitalizations achieve AUC 0.983 for death versus recovery prediction and identify eosinopenia as a top predictor via SHAP.