Deep Learning-Based Dynamic Risk Prediction of Venous Thromboembolism for Patients With Ovarian Cancer in Real-World Settings From Electronic Health Records Data collected in the multicentric PRAIS ...
Recent progress in survival analysis has been driven by the integration of machine learning techniques with traditional statistical models, such as the Cox proportional hazards model. This synthesis ...
Machine learning models showed strong predictive performance for 5-year survival in stage III colorectal cancer patients, with AUC values between 0.766 and 0.791. Key prognostic factors identified ...
The question of whether prehospital emergency anaesthesia and intubation improves survival in patients with major trauma has ...
Clinical application of individualized tumor-informed circulating tumor DNA for therapeutic response and relapse prediction in patients with neuroblastoma. This is an ASCO Meeting Abstract from the ...
Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
A UCLA-led team has developed a machine-learning model that can predict with a high degree of accuracy the short-term survival of dialysis patients on Continuous Renal Replacement Therapy (CRRT). CRRT ...