Maryland Researchers Combine AI, Medicine on Major Health Challenges

Four joint research projects taking aim at major health care challenges have been awarded up to $1.8 million over three years through a new program that brings together experts in medicine and artificial intelligence at the University of Maryland, Baltimore (UMB) and the University of Maryland, College Park (UMCP).

Known as AIM-HI (AI + Medicine for High Impact), the program was launched a year ago by Laurie Locascio, vice president for research at both UMB and UMCP, in partnership with deans from both campuses and support from both university presidents.

“The AIM-HI program unites unique strengths from both campuses in pursuit of breakthrough efforts that will impact and improve human health,” Locascio said.  “These teams of investigators are partnering to address major health care challenges. I have big expectations for what these teams will be able to accomplish and the impact that it will have on Marylanders and around the world.”

The new grants support UMD-UMB teams that are investigating new approaches in four areas: chronic pain, mental health, aging and age-associated diseases, and neonatal opioid withdrawal syndrome. 

“The AIM-HI program represents some of our best research collaboration, leveraging our strengths to address real-world healthcare challenges,” said UMB President Bruce Jarrell. “Not only will this partnering of expertise in medicine and computer science yield new knowledge and new treatments, but it will also lead to countless new collaborations, as we all see what is possible when we work together.” 

AIM-HI supports research with strong potential to contribute major scientific discoveries, secure sizable additional external funding and ultimately improve the quality of the life for people in Maryland, the region and the nation through improved patient care or treatment. 

“With these projects, we are developing new technologies and approaches to relieve some of the most painful and difficult ailments that afflict people in the state,” said UMD President Wallace D. Loh. “The progress we make will demonstrate the power of partnership—the edge that our institutions working together can deliver to Maryland and beyond.”

The four funded projects are:

“Development of a Predictive Multi-omics Platform for the Study of Aging and Age-associated Diseases” seeks to develop an analytical framework to identify predictive functional relationships between changes in different metabolic parameters during aging. The ultimate goal is to generate testable hypotheses about mechanisms contributing to aging under normal and disease conditions and identification of appropriate interventions. 
UMB researchers: Maureen Kane, School of Pharmacy-Pharmaceutical Sciences; Marta Lipinski, School of Medicine-Department of Anesthesiology and the Shock, Trauma and Anesthesiology Research (STAR) Center; Jace Jones, School of Pharmacy-Department of Pharmaceutical Sciences
UMCP researcher: Michael Cummings, Department of Biology and University of Maryland Institute for Advanced Computer Studies (UMIACS).

“Precision Therapy for Neonatal Opioid Withdrawal Syndrome” aims to improve clinical decision making in the treatment of this syndrome, including the development of clinical and genomic biomarkers to predict withdrawal and treatment response in a unique, racially diverse cohort at the University of Maryland Medical Center and affiliated hospitals. 
UMB researchers: Seth Ament, School of Medicine-Institute for Genome Sciences and Department of Psychiatry; Dina El Metwally School of Medicine’s Department of Pediatrics and director of the University of Maryland Medical Center’s Neonatal Intensive Care Unit; Amber Beitelshees, School of Medicine’s Program for Personalized and Genomic Medicine and Department of Medicine; Asaf Keller School of Medicine and chair of the Department of Anatomy and Neurobiology
UMD Researchers: Margret Bjarnadottir, Department of Management Science and Statistics; Ritu Agarwal, interim dean of the Robert H. Smith School of Business and chair of the Department of Information Systems

“A Multi-Stage Machine Learning Framework for Prioritization in Mental Health Risk Assessment” seeks to lead a shift in thinking about machine learning in mental health by treating the dominant paradigm of individual-level classification or regression not as an end in itself, but rather as providing necessary components in a broader framework, where the central need is to prioritize available resources effectively, given real-world resource constraints.
UMB researcher: Deanna L. Kelly, School of Medicine’s Department of Psychiatry and Maryland Psychiatric Research Center
UMD researchers: Philip Resnik, Department of Linguistics and UMIACS; Carol Espy-Wilson, Department of Electrical and Computer Engineering; John Dickerson, Department of Computer Science and UMIACS

“Tackling Chronic Pain: Machine Learning-Enabled Biomarker Discovery and Sensing” will search for novel, localized biomarkers associated with gastrointestinal pain by: 1) mass spectrometry imaging as well as proteomic, lipidomic and RNA sequence analysis; 2) miniaturized, multiplexed biochemical sensors to measure localized biomarkers; 3) machine learning
UMB Researchers: Robert Ernst, School of Dentistry’s Department of Microbial Pathogenesis; Richard Traub, School of Dentistry’s Department of Neural and Pain Sciences; Alison Scott, School of Dentistry’s Department of Microbial Pathogenesis
UMD Researchers: Pamela Abshire, Department of Electrical and Computer Engineering and Institute for Systems Research (ISR); Reza Ghodssi, Department of  Electrical and Computer Engineering and ISR; Behtash Babadi, Department of Electrical and Computer Engineering and ISR