PhaseV to Present Novel Causal Machine Learning Method for Understanding Patient Treatment Response at ML4H Symposium [Video]

New Method, Applicable to Multiple Therapeutic Areas and Clinical Phases, Can Advance Precision Medicine for Improved Patient Outcomes

BOSTON, Dec. 12, 2024 /PRNewswire/ — PhaseV, a pioneer in software and machine learning (ML) for advanced clinical trial optimization, announced today it will present at the AHLI Machine Learning for Health (ML4H) 2024 Symposium, taking place on December 15-16 in Vancouver, Canada. The company has been selected to share a poster session on its novel method for identifying responders in clinical trials and observational studies. PhaseV will also demonstrate the power of its machine learning-driven platform to enhance adaptive clinical trial design in a demo presentation.

The conference session, Identifying Responders in Randomized Controlled Trials and Observational Studies, will explore PhaseV’s novel Causal Responder Detection (CARD) method. Published in a recent research paper, this approach uses advanced machine learning methods, specifically causal …