A team led by FAU’s Wazir Muhammad will incorporate artificial intelligence, specifically deep reinforcement learning, to create a prototype of a dynamic digital twin of cancer patients to better understand and treat their disease using personalized radiation therapy. The digital twin will incorporate simulation, model inference, data assimilation, and high-performance computing.
“The goal of the model is to provide optimized treatment plans, aid diagnosis and follow-up, and draw on patients’ data including health history, cancer histology, genomic and molecular profiling, prior treatment history, and radio-sensitivity index to improve patient outcomes,” says Muhammad. The project will address challenges related to data quality, complexity and integration of AI into clinical workflows.
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