University of Maryland Institute to Apply AI to Healthcare

Published 11/17/22 in Healthcare Innovation

A newly announced University of Maryland Institute for Health Computing will seek to leverage advances in artificial intelligence (AI) and computing to create a learning healthcare system that evaluates both de-identified and secure digitized medical health data to diagnose, prevent and treat diseases in patients across the state of Maryland.

The Institute is the result of a partnership between the University of Maryland, Baltimore (UMB) and the University of Maryland, College Park (UMCP), in collaboration with the University of Maryland Medical System (UMMS) and Montgomery County, Md.

In a statement, University System of Maryland Chancellor Jay Perman, M.D., said the biomedical triumvirate of UMB’s top-ranked health science professional schools; College Park’s state-of-the-art expertise in artificial intelligence, virtual reality, and machine learning; and UMMS, which serves over 5 million patients, all linked through the electronic healthcare records, is an indication of great things on the horizon in healthcare innovation.

The Institute “joins together the deep expertise of the University of Maryland in advanced computing, and the equally deep expertise of UMB and UMMS in human health,” said Perman. “When you leverage the first – advanced computing – to the second – our health – it’s a wonderful thing.”

The Institute will use machine learning to study emerging diseases and help establish precision patient care to halt disease progression. For example, poorly controlled diabetes, high blood pressure, risk of opioid overdose, and early kidney disease can be identified by trending changes in lab tests in outpatients, allowing targeted interventions to prevent disease progression.

Mohan Suntha, M.D., M.B.A., president and CEO of UMMS noted he is proud of the partnership the system’s 12 afilliated hospitals have within the university-based health system. “While we are delivering the care of today, we take on the responsibility of educating the future healthcare workforce,” he said in a statement. “We do this through partnership and so when I look around today, I am incredibly excited about the partners that sit together to make this announcement,” he continued.

The Institute hopes to catalyze a clinical data science ecosystem at North Bethesda that draws FDA and NIH investigators, UMB and UMCP faculty, medical bioinformatic educational programs and students, and industry partners, allowing expansion of computational “dry” laboratories, virtual meeting rooms and classrooms.

The Institute is expected to open in leased space in early 2023, with final completion of laboratory and office space at the North Bethesda Metro location in 2028. Initial funding of $25 million is provided by University of Maryland Strategic Partnership: Empowering the State (MPower). Montgomery County government will provide an additional $40 million to develop the North Bethesda site.

In addition to the new Institute, the University of Maryland Medicine System announced last year that it was partnering with health tech company Vibrent Health to create the All of Maryland Precision Health Initiative, a statewide digital platform for studies examining how genes and other factors affect health.

The mission of All of Maryland — a study that is being led by University of Maryland School of Medicine (UMSOM) researchers — is to discover better ways to individualize healthcare. The goal is to enable individuals to benefit from treatments tailored to their own health profiles.

This data-driven study aims to enroll up to 250,000 volunteers across Maryland in order to identify and better understand the health needs of Marylanders by region and community. A particular focus will be on underserved populations who experience significant health disparities, causing more illness and shorter lifespans. The large-scale effort to collect broad sources of health data, including genetic information, will aid researchers in better understanding human genomic variation and its relationship to disease and treatment.