Kudithipudi is M-POWER’s lead principal investigator and is the founding director of the MATRIX AI Consortium for Human Well-Being.
She added, “Our collaborative approach brings together clinicians, health care practitioners, AI and machine learning designers and public health experts under one umbrella to promote a more inclusive health care landscape. The solutions we develop are relatively disease-agnostic and cater to AI users of varying skill levels. This center will not only position us to lead the national AI dialogue but also prepare our students in an exceptionally competitive area.”
The launch of M-POWER will offer clinicians and researchers the opportunity to train with emerging technology such as open-source AI and machine learning toolkits to better diagnose and address health disparities including heart disease and obesity. Their work will begin in Texas before expanding nationwide to anyone working in health care or biomedical data.
The project is supported by a team of UTSA faculty and MATRIX thrust leads, including Amina Qutub, Ambika Mathur, Kevin Desai, Panagiotis Markopoulos, Anandi Dutta and Erica Sosa along with UT Health San Antonio professor Mark P. Goldberg, MD.
The researchers will pursue a transdisciplinary approach.
Qutub, the Burzik Professor in Engineering Design and associate professor in the UTSA Department of Biomedical Engineering and Chemical Engineering, will bring her knowledge of neurology and systems biology to the center, as well as her experience in augmenting human capabilities through AI. Desai, Markopoulos and Dutta will contribute their multidisciplinary expertise in machine learning model design and training.
Sosa’s expertise is in Latino health, public health and community-engagement. Goldberg, a neurologist, will help with new collaborations in the health care community and clinical healthcare flows.
“It’s really exciting to see how AI is transforming recovery for different disorders and also enhancing preventative medicine,” Qutub said. “I look forward to empowering clinicians and researchers to make an impact in health with AI —to transform how we treat and prevent health conditions in every individual. All of us are unique, so what can we do differently to improve our health? AI can inform individual care in ways where a doctor or nutritionist looking at information manually wouldn’t be able to.”
Traditionally, the use of AI and machine learning tools has been limited to niche health care environments, but they are becoming more broadly adopted because of their ability to handle larger quantities of data faster than humans and their increasing accuracy in predicting novel situations.
New approaches using generative AI in post-stroke treatment, for example, have caught the attention of health care practitioners, Qutub explained.
“A stroke is more prevalent in populations where there are metabolic disorders. More broadly, many socioenvironmental factors affect stroke risks and recovery, as well as risks for other neurodegenerative disorders,” Qutub said. “As one example, obesity disproportionally affects the Hispanic population within San Antonio. The AI platform we’re developing would help people who are using health data and molecular data to understand obesity and ward off its neurological risks.”
UTSA’s NIH award aims to build an infrastructure where clinicians have ready access to AI and machine learning tools that improve data interpretation and lead to new approaches for therapy, from the molecular level to behavior.
The researchers are developing educational pathways, courses and workshops as part of the grant to improve accessibility to AI, machine learning tools and research. The series of tutorials and workshops explore AI technologies with a special focus on large language models, including ChatGPT and computer vision tailored for medical data analysis.
“Participants will delve into sophisticated AI algorithms to be used with complex medical datasets, gaining insights into how large language models excel in processing textual medical records, research findings and patient notes,” Desai explained. “We’ll explore computer vision techniques and their ability to extract crucial insights from medical images such as X-rays, MRIs, and CT scans. Through interactive exercises and compelling case studies, attendees will not only grasp the technical nuances but also explore the AI adoption within health care settings.”
UTSA students will be given opportunities to train with such tools to improve health and biomedical applications, and better equip them for careers as medicine evolves.
Desai and Dutta will conduct tutorials for the clinicians in both the UT Health San Antonio and the broader AIM-AHEAD communities.
“In this age of emerging AI, machine learning and ChatGPT, it’s crucial for our students to receive instruction and conduct research into optimal ways to harness these tools and advance state of the art technology to create a well-informed workforce,” said Mathur, senior vice provost for UTSA graduate and postdoctoral studies and graduate school dean.
“UTSA’s students will be positioned through this program to positively impact health care delivery to the San Antonio and national population,” Mathur continued. “We are extremely grateful to the NIH for recognizing UTSA’s expertise in this domain and awarding us this funding mechanism to prepare our students.”
UTSA is striving to become the frontrunner in health care and AI.
The MATRIX is a pioneering consortium of more than 70 faculty investing in development of AI for applications to human well-being. MATRIX’s mission is to conduct transformative research in the design, use, and deployment of AI that enhances human life, and to offer rigorous research training opportunities that transcend disciplinary boundaries.
