A machine learning model generated by a team from the European Society for Blood and Marrow Transplantation (EBMT) outperformed standard statistical models in identifying and stratifying ...

The study put NetraAI, DeepSeek, ChatGPT, and traditional machine learning models to the test using three, complex clinical trial datasets: CATIE (focused on schizophrenia), CAN-BIND (focused on ...

Achieved model accuracy of 90–95% on stratified subgroups, significantly outperforming traditional machine learning baselines. Persona-specific analyses revealed clear survival curve separations, ...

The findings revealed that machine learning methods, especially GAN-based and time-series imputation techniques like CATSI, often outperformed traditional statistical methods in addressing missing ...

NetraAI also outperformed traditional machine learning techniques in identifying clinically meaningful patient subgroups from real-world clinical trial data. TORONTO, June 23 ... The study put NetraAI ...

An international team led by Einstein Professor Cecilia Clementi in the Department of Physics at Freie Universität Berlin introduces a breakthrough in protein simulation.

NetraAI also outperformed traditional machine learning techniques in identifying clinically meaningful patient subgroups from real-world clinical trial data. June 23, 2025 11 min read ...