![]() ![]() Stewart said the team will recruit participants from underserved groups – such as rural and first-generation students - in STEM. ‘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.” “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. “My focus is on improving access to STEM careers for West Virginians,” Stewart said. Gay Stewart, a physicist who directs the WVU Center for Excellence in STEM Education, is another co-investigator. “With this program, we will contribute to the training of a new generation of engineers, scientists and healthcare professionals able to better bridge the knowledge and communication barriers that separate them, with a focus on creating synergies around the use of artificial intelligence to generate and leverage data for improving healthcare delivery and outcome.” “The problem is that healthcare professionals have limited digital skills when it comes to exploring engineering solutions to improve healthcare delivery, while engineers with strong digital backgrounds lack the healthcare knowledge to propose new tools exploiting medical data,” Doretto said. The project anticipates training 24 funded and 40 unfunded master’s and doctoral students from different disciplines including engineering, computer science, medicine, health sciences, physical sciences and economics.Ī co-investigator on the project within the Statler College is Gianfranco Doretto, who will teach some of the classes related to data science and A.I. ![]() techniques in addressing digital health issues. The NSF funding will help establish a new graduate education and traineeship model to prepare students to work in collaborative teams to develop and apply data science and A.I. “These methods have shown performance that are close to human performance, and at times outperform human professionals on some of these tasks,” he said. techniques on health problems including breast cancer detection, diagnosing eye diseases, reading cardiac ultrasound images, early prediction of acute kidney failure, predicting adverse drug events and visualization of neuronal structures in the brain. 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.”Īdjeroh noted that various recent reports, including results from WVU labs, document the success stories of A.I. ![]() “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. 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),” Adjeroh said. “Two of our pathway themes in the project are focused on the use of data science and A.I. “Bridges in Digital Health,” which recently received $3 million from the National Science Foundation, hopes to address the combination of rising healthcare costs, the expansion of the nation’s elderly population and health disparities, particularly in rural communities, through advances in digital health and artificial intelligence, and training the next generation of professionals to develop and deploy such advances.ĭigital health is a rapidly growing field that involves clinical and biomedical data including prescriptions, medical images, ultrasound videos, electronic health records 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. ![]()
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