Artificial intelligence continues to transform biomedical research by enabling the analysis of vast datasets, identifying patterns and accelerating discoveries. Through machine learning and predictive modeling, AI aids in drug development, genetic research and disease understanding, fostering innovative solutions and advancing precision medicine for improved healthcare outcomes.
In the clinical field, few medical specialties have realized as much benefit from artificial intelligence as radiology. This field continues to use AI to enhance diagnostic accuracy and efficiency. By integrating advanced algorithms and machine learning, AI assists St. Jude radiologists in detecting anomalies, interpreting imaging data, and streamlining workflows, ultimately improving patient care and enabling more precise and timely medical interventions.
To schedule an interview with one of our experts, email media@stjude.org.
Artificial Intelligence Experts
-
Andrew D. Smith, MD, PhD
Smith
Andrew Smith, MD, PhD, St. Jude Department of Radiology chair, is a nationally recognized academic abdominal and oncologic radiologist with expertise in the application of artificial intelligence (AI) in diagnostic imaging and medicine. His research interests include clinical applications of machine learning in radiology, AI for tumor response evaluation and detection of cancer, AI for opportunistic screening of diseases and the use of large language models in radiology reporting.
Smith is the primary investigator of AI MINER, Artificial Intelligence Multi-Institutional Network for Ethical Research. He is an inventor on 30 patents and has led FDA clearance on a number of AI and imaging technology devices.
-
Ed Suh, PhD
Suh
Ed Suh, PhD, vice president for research informatics at St. Jude, heads the Research Information Services group. His team is responsible for deploying and regulating high-performance AI computing resources for the hospital’s scientific research enterprise. Suh’s colleagues are assisting the new St. Jude Office of Data Science to develop a variety of AI systems and tools, including AI models and inferencing engines. Suh has held information science leadership posts at MD Anderson Cancer Center, TGen (City of Hope) and the National Institutes of Health.
-
Paul Yi, MD
Yi
Paul Yi, MD, St. Jude Department of Radiology, is a practitioner of diagnostic imaging. The field of radiology and diagnostic imaging has been a proving ground for medical applications of artificial intelligence for a number of years. As a physician-scientist, Yi’s research interests include the development and application of AI and deep learning towards medical imaging applications, with special interest in evaluating the trustworthiness and fairness of deep learning models.
