Reviewed by Alex SmithOct 27 2021
Quality healthcare goes beyond the medical profession, as demonstrated by a new project directed by West Virginia University (WVU) which includes not only health experts but also engineers, a lawyer, a physicist, and a business data analyst.
A multidisciplinary team at WVU will embark on a project that will leverage artificial intelligence and digital health—which includes data from mobile devices and wearables—to address rising healthcare costs, the expansion of the nation’s elderly population, and health disparities. Image Credit: WVU Illustration/Aira Burkhart.
Recently awarded $3 million by the National Science Foundation (NSF), “Bridges in Digital Health,” aims to find answers to the combination of growing healthcare costs, the expansion of the country’s elderly population, and health inequalities, predominantly in rural communities, via advances in digital health and artificial intelligence (AI), and training the next generation of specialists to develop and use such advances.
Digital health is a quickly expanding field that covers clinical and biomedical data including prescriptions, electronic health records, ultrasound videos, medical images, and data from mobile devices and wearables, such as Fitbit, said Donald Adjeroh, lead investigator of the project and professor and associate chair in the Lane Department of Computer Science and Electrical Engineering.
Two of our pathway themes in the project are focused on the use of data science and A.I. on two key areas in healthcare: namely, cardiovascular health (analysis of cardiac images, especially, echocardiograms), and genomics (analysis and functional annotation of long non-coding ribonucleic acids—a type of RNA—and their role in disease prediction and prognosis).
Donald Adjeroh, Project Lead Investigator, Professor and Associate Chair, Lane Department of Computer Science and Electrical Engineering, WVU
“Apart from traditional electronic health records, our health data will come from different sources and devices, including wearable devices such as hand-held mobile cardiac ultrasound devices, or pocket EKG monitors, low-cost mobile activity monitors, Fitbits, smart watches, social media, etc.,” Adjeroh added.
Such low-cost wearable devices and data sources are important in collecting health-related data from individuals in rural areas, and outside the hospital setting, important for preventive care.
Donald Adjeroh, Project Lead Investigator, Professor and Associate Chair, Lane Department of Computer Science and Electrical Engineering, WVU
Adjeroh pinpointed that several recent reports, including results from WVU labs, record the success stories of A.I. methods on health issues such as diagnosing eye diseases, breast cancer detection, early prediction of acute kidney failure, predicting adverse drug events, reading cardiac ultrasound images, and visualization of neuronal structures in the brain.
“These methods have shown performance that are close to human performance, and at times outperform human professionals on some of these tasks,” he said.
The NSF funding will help set up a new graduate education and traineeship model to train students to participate in collaborative teams to design and apply data science and A.I. methods in resolving digital health problems.
The project expects to train 24 funded and 40 unfunded doctoral and master’s students from various disciplines including physical sciences, engineering, medicine, health sciences, computer science, and economics.
My focus is on improving access to STEM careers for West Virginians.
Gay Stewart, Project Co-Investigator, Physicist, and Director, Center for Excellence in STEM Education, WVU
Stewart continued, “Much of my focus has been on building the pipeline earlier, but traditional graduate programs do not provide the ability to work across disciplinary silos deeply enough to make the advances we need. ‘Bridges’ will address these challenges, by preparing trainees to work effectively in transdisciplinary teams that develop leading technology-driven solutions to challenging problems in DH, especially in rural communities.”
Stewart stated the team will employ participants from underserved groups—such as first-generation and rural students —in STEM.
“First-generation students tend to graduate college in STEM at lower rates than their peers and are less likely to pursue graduate studies,” she said. “Yet, we need their voices in this important work. I envision a much stronger motivation to pursue advanced studies when students can see the potential for significant impact on their families and communities.”
Dr. Michael Ruppert, another co-investigator on the project, illustrated the role of the investigation from a biomedical perspective.
One of the stumbling blocks for biomedical researchers is that very diverse skill sets are required to develop new knowledge by analyzing large datasets such as clinical data. For example, you have to be good at biomedicine, which often involves moving molecules around the lab, and you also have to be able to move very large digital datasets around as well. The goal is to cross train so as to generate students with all the necessary skill sets.
Dr Michael Ruppert, Project Co-Investigator and Jo and Ben Statler Chair of Breast Cancer Research, WVU Cancer Institute
He is also a professor of biochemistry in the School of Medicine.
Other members of the study team include Gianfranco Doretto, computer science and electrical engineering; Dr. Partho Sengupta, of Rutgers University; Michael Schaller, biochemistry; Valarie Blake, law; Brad Price, management information systems; Michael Hu, microbiology, immunology, and cell biology; Xin Li, Nasser Nasrabadi, Don McLaughlin, and Brian Powell, all of computer science and electrical engineering; and Cathy Morton, Health Sciences and Technology Academy.