CLIC Un-Meeting: Applications for Machine Learning & Artificial Intelligence in Translational Science

John Schlia Photography

On Saturday, June 1, 95 researchers, academic faculty, informaticians and clinicians from across the country gathered at the University of Rochester Medical Center to discuss applications for machine learning (ML) and artificial intelligence (AI) in translational science. Attendees from 45 CTSA Program hubs in 27 states and D.C. convened to discuss the potential applications of AI and ML for translational science and forge new partnerships with the goal of leveraging technological innovations in research. 

The “Un-Meeting: Machine Learning & Artificial Intelligence Applications in Translational Science,” hosted by the Center for Leading Innovation and Collaboration (CLIC), kicked off with 4 minute presentations from subject matter experts to help frame the issues and identify key topics of discussion. Amar Das, M.D., Ph.D., IBM, M. Ehsan Hoque, Ph.D, University of Rochester, Erich Huang, M.D., Ph.D, Duke University School of Medicine, Gang Luo, Ph.D, University of Washington, Parsa Mirhaji, M.D., Ph.D, Albert Einstein College of Medicine, Ram Samudrala, Ph.D, State University of NY at Buffalo, Shyam Visweswaran, M.D., Ph.D and Chunhua Weng, Ph.D, FACMI, Columbia University were among the presenters.

“There’s been this explosion of applying AI, machine learning, deep learning and algorithmic classification to problems in health and medicine. But there are a number of issues and questions that people have in this area that the clinical and translational science community can bring expertise to,” said Martin Zand M.D., Ph.D., CLIC co-director. “The opportunity to help create an agenda with all of your other conference participants and then to participate in the sessions that you want to fosters engagement that lasts far beyond the meeting itself.”

The format of the Un-Meeting was designed to create a collaborative environment that promotes opportunities for attendees with different backgrounds and expertise to network, share and brainstorm. The goal was for these experts to generate new research avenues and collaborations that capitalize on the benefits of ML and AI – with the ultimate goal of following through on that research. Allowing participants to sculpt the agenda of the meeting created a shared sentiment of excitement in attendees, despite not knowing exactly what the day would hold.

Following the morning presentations, event attendees collaborated on approaches to tapping into the potential of ML and AI through idea generation and breakout sessions. The sessions focused on topics like ML algorithmic bias, clinical implementation of AI and ML, mobile sensor data, AI genomics phenotyping, time series ML methods, AI model life cycle management, drug modeling and prediction, ML ethics and much more.

From this event, CLIC hopes that other CTSA Program hubs will be inspired to host their own Un-Meetings, ultimately encouraging scientists and researchers to come together to tackle critical public health issues that no one team can overcome in isolation. If you’re interested in hosting an upcoming Un-Meeting, CLIC is now accepting applications for future events. You can apply here. If you’re interested in learning more about the Un-Meeting concept, please contact CLIC.

You can also find additional materials from this specific event, including speaker presentations, a briefing book and a list of funding opportunities, on the CLIC website


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