Transformative Applications of Artificial Intelligence in Medicine: Drug targeting Disease-affected Microenvironments and Automated Stroke Detection, Diagnosis, and Treatment

Speaker 

Dr. Wong holds the John S. Dunn, Sr. Distinguished Endowed Chair in Biomedical Engineering; he is also a Professor of Radiology, Pathology, Laboratory Medicine, Neurology, and Neurosciences, the Associate Director of Translational Research at Methodist Cancer Center, and Chief of Medical Physics and Chief Research Information Officer at Houston Methodist Hospital.

In addition, he serves as the Founding Director of the Ting Tsung and Wei Fong Chao Center for BRAIN and Founding Director of the Center for Modeling Cancer Development at Houston Methodist Research Institute. He also holds a dozen of other academic posts across institutions in Texas Medical Center as well as overseas universities and medical schools.

Abstract 

Artificial intelligence (AI) is poised to revolutionize medical research, education, and clinical practice by harnessing vast, multi-modal data sets, cutting-edge biotechnologies, and unparalleled computational capabilities. Its potential to automate tasks, enhance efficiency, improve access, and foster innovation has already been demonstrated. However, the capacity of AI to tackle complex challenges, which traditionally rely on the nuanced cognitive skills of clinicians and researchers to analyze and interpret extensive, multimodal data at various scales, remains an area of exploration. This presentation explores two pivotal AI applications in medicine: drug discovery focusing on disease-specific microenvironments, and the use of cognitive AI technologies for the comprehensive management of acute stroke, including its detection, diagnosis, and treatment. Through these case studies, we aim to spark insightful discussions on AI's transformative impact on medical research and practice. Furthermore, the success of cognitive automation in healthcare prompts a reevaluation of the roles of physicians, reshaping the patient-doctor dynamic and the overall patient experience.