Predicting Post-Hepatectomy Liver Failure with the PILOT Architecture: Integrating Liver Regeneration Biomarkers and Time-Phased Machine Learning

Predicting Post-Hepatectomy Liver Failure with the PILOT Architecture: Integrating Liver Regeneration Biomarkers and Time-Phased Machine Learning

The novel PILOT machine learning architecture integrates time-phased perioperative data and regeneration-associated biomarkers to predict post-hepatectomy liver failure within six hours of surgery, significantly outperforming traditional clinical models and enabling early personalized risk stratification.
Precision Rehabilitation: Machine Learning Reveals Why ‘Early Mobilization’ Fails Some ICU Patients While Saving Others

Precision Rehabilitation: Machine Learning Reveals Why ‘Early Mobilization’ Fails Some ICU Patients While Saving Others

A secondary analysis of the TEAM trial using machine learning demonstrates that enhanced early mobilization in mechanically ventilated patients has highly individualized effects, ranging from a 34% mortality reduction to a 39% increase in risk, depending on baseline clinical characteristics.
Advancing Precision Medicine in Hepatocellular Carcinoma: Machine Learning Radiomic Models Surpass Clinical Biomarkers in Predicting Immunotherapy Outcomes

Advancing Precision Medicine in Hepatocellular Carcinoma: Machine Learning Radiomic Models Surpass Clinical Biomarkers in Predicting Immunotherapy Outcomes

Integrated radiomic-clinical machine learning models outperform traditional clinical biomarkers in predicting survival and treatment response in unresectable hepatocellular carcinoma patients undergoing atezolizumab plus bevacizumab therapy.