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 ...

Unraveling survival disparities in primary central nervous system (CNS) lymphoma: An analysis of race, socioeconomic factors, and treatment outcomes using the Surveillance, Epidemiology, and End ...

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 ...

PLSKB: An Interactive Knowledge Base to Support Diagnosis, Treatment, and Screening of Lynch Syndrome on the Basis of Precision Oncology We used an innovative machine learning approach to analyze ...

Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...

In recent years, JupyterLab has rapidly become the tool of choice for data scientists, machine learning (ML) practitioners, and analysts worldwide. This powerful, web-based integrated development ...

Chemists have created a machine learning tool that can identify the chemical composition of dried salt solutions from an image with 99% accuracy. By using robotics to prepare thousands of samples and ...

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...