UTHealth Houston: Pioneering generative AI in health care
By leveraging cutting-edge technology and revolutionizing patient care, research, and operational efficiency, UTHealth Houston has emerged as a trailblazer in the lightning-fast development and application of generative artificial intelligence (AI) on the health care industry.
Hosted by McWilliams School of Biomedical Informatics at UTHealth Houston, the inaugural “Generative AI Now!” workshop was held on Wednesday, May 29, with a full crowd. Leaders from the Houston area and the Texas Medical Center attended, including representatives from other institutions such as the University of Houston, Baylor College of Medicine, Texas Children’s Hospital, and more.
The keynote speech was given by Dean Sittig, PhD, professor in the Department of Clinical and Health Informatics at McWilliams School of Biomedical Informatics. Sittig reviewed the basics of generative AI, current regulations, and ethical issues, as well as patient safety and risk management concerns.
Susan Fenton, PhD, presented on the current and future policy landscape. Fenton is professor and vice dean for education, director of the Center for Quality Health IT Improvement, and the Dr. Doris L Ross Professor at the school.
Xiaoqian Jiang, PhD, professor and chair of the Department of Health Data Science and Artificial Intelligence at McWilliams School of Biomedical Informatics and associate vice president for Medical AI at UTHealth Houston, spoke about real-world applications and showcased current projects and research at the school. Jiang is also the Christopher Sarofim Family Professor in Biomedical Informatics and Bioengineering, and serves as the director of the Center for Secure Artificial Intelligence For Healthcare.
The event concluded with an interactive lab for participants on effective prompt engineering.
“UTHealth Houston is committed to responsible AI usage as we look to position ourselves as a leader in health care transformation,” said Jiajie Zhang, PhD, dean and The Glassell Family Foundation Distinguished Chair in Informatics Excellence at McWilliams School of Biomedical Informatics. “By harnessing generative AI, we are not only improving patient care but also shaping the future of medicine. As other institutions follow suit, the health care landscape will continue to evolve, driven by innovation and ethical considerations.”
Following the workshop in Houston, The University of Texas System hosted its inaugural two-day AI Symposium in health care as leaders from all UT System health institutions and medical schools convened at UT Southwestern Medical Center in Dallas.
The symposium was co-chaired by Hongfang Liu, PhD, professor in the Department of Health Data Science and Artificial Intelligence and D. Bradley McWilliams Chair at McWilliams School of Biomedical Informatics and vice president of learning health systems at UTHealth Houston. The university was well represented at the event, with several faculty members involved in discussions, including Zhang, Jiang, and Fenton. Others participating included Degui Zhi, PhD, MS, chair of the Department of Bioinformatics and Systems Medicine and Glassell Family Professor, and Elmer Bernstam, MD, MSE, associate dean for research, professor in the Department of Clinical and Health Informatics, and the Reynolds and Reynolds Professorship in Clinical Informatics. Zhi and Bernstam are also faculty members of MD Anderson Cancer Center UTHealth Houston Graduate School of Biomedical Sciences. Amar Yousif, MBA, vice president and chief information officer at UTHealth Houston, participated on a panel about AI ethics and regulations.
The Dallas event brought together experts in artificial intelligence from across the UT System’s broad health care enterprise to explore the emergence of AI, as it begins to reshape health care and revolutionize everything from scientific discovery and drug development, to diagnosis and treatment, to patient care and administrative processes.
“From an IT perspective, it is extremely important that we continue to stay on top of this ever-changing landscape, because our students, staff, and faculty have many questions about how to properly use the tools,” Yousif said. “To do that, we have formed an AI Advisory Subcommittee of executives and leaders within our university, to help guide us down this road.”
UTHealth Houston has been building its own generative AI model based on large-scale real-world data, with potential downstream applications including re-admission prediction, workflow optimization, and better patient care.
“What a time to be in medicine, to have the opportunity to see how we can utilize these technologies to help ease the work of doctors and nurses, and to try and make the world a healthier place,” said Babatope Fatuyi, MD, UTHealth Houston chief medical information officer, who attended the workshop. “I love that we, as a university, are leading the discussion in that regard.”
While the benefits of generative AI are substantial, there are ethical implications that UTHealth Houston leadership is well aware of. Responsible use of AI tools is crucial to maintaining patient trust and ensuring accurate outcomes.
“We are committed to transparency in AI utilization, emphasizing that critical thinking and clinical judgment remain essential, prioritizing patient safety, and educating our staff on AI capabilities, limitations, and ethical considerations,” Zhang said. “But, the recent wave of AI innovations, in my opinion, is truly a ‘Cognitive Revolution’ that is solving complex cognitive tasks on an industrial scale, freeing humans from a wide variety of cognitive labor. It’s as transformative as the Industrial Revolution, which liberated people from physical toil with engines, and the Agricultural Revolution, which addressed the biological issue of hunger through farming crops and livestock. It is imperative that we embrace it, now.”
UTHealth Houston continues to explore the potential of generative AI as well as other AI innovations across various health care domains, including multimodal models, regulatory compliance with evolving guidelines, and patient-centric AI.
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