Malone team wins Provost’s DELTA grant for new course on AI in healthcare
A team of researchers from the Malone Center for Engineering in Healthcare (MCEH) has been awarded a DELTA grant from the JHU’s Office of the Provost to develop an online course about machine learning aimed at those working in the healthcare research field.
Machine learning (ML) & artificial intelligence (AI) frameworks are expected to play a significant role in driving innovation and discovery in healthcare research. Examples of ML & AI applications in health care include medical imaging and diagnostics, robot-assisted surgeries, and remote care assistance.
To foster research collaborations using ML & AI, we must bridge the knowledge gap between healthcare decision-makers and engineers/data scientists. Specifically, both groups should understand ML & AI methods and how algorithms are validated for healthcare applications.
With the support of the grant, the Malone team will develop an online course to equip both Hopkins clinicians and engineers with the skills to design, analyze, interpret, and report research on ML & AI in health care.
The research team includes S. Swaroop Vedula (MCEH), assistant research professor; Anand Malpani (MCEH), assistant research scientist; Gregory Hager (MCEH, Computer Science); Mathias Unberath (MCEH, Computer Science); and Brian Caffo (MCEH, Biostatistics).
According to the team, a major goal of the project is to support two of JHU’s “Ten by Twenty” priorities: to strengthen interdisciplinary collaboration between medicine and engineering, and enable the university to shape the future of healthcare innovations using engineering and technology.
The DELTA program, now in its second year, was established to support new digital technology initiatives that enhance teaching and learning at Johns Hopkins. This year, the seven winning projects – selected from 43 initial proposals – included a 3D model for neonatal surgery training, a new platform to create online lectures, and an obstetric triage web app.