UAB Researcher Uses Artificial Intelligence Models in Cancer Treatment
UAB researcher Neil Pfister is working to understand cancer treatment responses and expand precision medicine applications using artificial intelligence infrastructures and foundational models.
Dr. Neil Pfister, from the UAB O'Neal Comprehensive Cancer Center and the Marnix E. Heersink School of Medicine, is working on artificial intelligence infrastructures and foundational models to predict how cancer patients will respond to treatments and to advance precision medicine.
Artificial Intelligence and Cancer Research
For decades, researchers have been striving to answer some of the most challenging questions in cancer care and understand why patients do or do not respond to treatments.
CURE AI and Clinical Data
Neil Pfister and his collaborators developed a deep learning framework called CURE AI to perform causal inference in clinical trial design, using genetic information and medical records.
Solutions for Rare Cancers
Pfister and his team are conducting pan-cancer analyses to more rapidly adapt therapies approved for common cancers to rare cancer types.
Model Architecture and Data Reliability
Researchers emphasize that instead of simulated patient data, true biological results can be obtained even from small patient numbers using correct model architectures in artificial intelligence models.
Benchmarking and Standardization
Benchmarking systems are critical for evaluating the efficiency of artificial intelligence models; in this context, Pfister conducts collaborative work with national groups such as the National Cancer Institute and the FDA.