Newswise — While chemotherapy has advanced in personalization, personalized radiation therapy for cancer remains underdeveloped. Current cancer treatment methods – including radiation therapy – are intricate, lack personalization, and rely heavily on the expertise of medical teams. Medical image analysis and machine learning hold great promise for enhancing personalized oncology.
However, challenges persist such as limited high-quality data and data complexity. Wazir Muhammad , Ph.D.
, principal investigator and an assistant professor in the Department of Physics within Florida Atlantic University ’s Charles E. Schmidt College of Science , has received a $701,000 grant from Precess Medical Derivatives, Inc., a company that specializes in providing an array of medical physics services and designing and developing software applications, for a project that aims to revolutionize cancer treatment by making it more personalized and effective.
The project, “Deciphering Digital Twins of Cancer Patients for Personalized Treatments,” uses artificial intelligence, in particular, deep reinforcement learning (DRL), to analyze multimodal data, and enhance cancer characterization and treatment to ultimately improve patient outcomes. “Using personal health data, genetic information about the tumor, and patient treatment and follow-up data, digital twins will simulate diagnoses and treatment options to help physicians choose the most effective treatments and monitor responses ove.