Artificial Intelligence (AI) is poised to transform healthcare, but its successful integration into healthcare requires careful consideration of regulatory frameworks, governance structures, data equity, and privacy protections. To help their academic community coalesce around this challenge, a team comprised of researchers from Lehigh University, Massachusetts General Hospital/Harvard Medical School, and Northwestern University's Feinberg School of Medicine are gathering researchers, clinicians, and industry experts in this space as part of the 2025 Spring Symposium Series sponsored by the Association for the Advancement of Artificial Intelligence (AAAI.) The team's "Leveraging AI to Revolutionize Healthcare" symposium will be a key portion of the 2025 AAAI Spring Symposium Series, set for Monday, March 31 through Wednesday, April 2, 2025, at the San Francisco Airport Marriott Waterfront in Burlingame, California.

Five multidisciplinary teams received seed grants to develop community-informed solutions for better health.

BUFFALO, NY — March 5, 2025 — A new research paper was published in Aging (Aging-US) on February 11, 2025, Volume 17, Issue 2, titled “Exposome-wide association study of environmental chemical exposures and epigenetic aging in the national health and nutrition examination survey.”

Identifying therapeutic gene targets is essential for advancing personalized medicine and addressing the genetic basis of diseases. However, traditional experimental methods for discovering these targets are costly and time-consuming. While deep learning has shown promise in identifying biomarker genes, it has struggled to identify therapeutic genes. To address this challenge, researchers have developed an innovative method, the Hypergraph Interactive Transformer, which accurately and quickly identifies therapeutic gene targets using hypergraphs and attention-based learning.

Researchers at the Carnegie Mellon University Robotics Institute and the Massachusetts Institute of Technology (MIT), created CHARCHA ( Computer Human Assessment for Recreating Characters with Human Actions), a secure and personalized verification protocol that allows an individual’s likeness to appear in generative video content. The team was inspired to create CHARCHA to respond to ethical issues in generative AI, such as unauthorized deepfakes. The CHARCHA system was inspired by CAPTCHA’s verification legacy. Whereas CAPTCHA uses text or image tests to differentiate between humans and bots, CHARCHA relies on real time physical interactions to differentiate between them. The program asks users to perform a set of randomized physical actions in front of a webcam, such as turning their head from left to right, squinting their eyes, or smiling with teeth. The live verification process, which takes about 90 seconds, analyzes the actions to ensure that the person is present and imitating the proper requests. By ensuring the person is interacting with the system, CHARCHA prevents pre-recorded video or still images from bypassing verification.

A pilot study in a rural Florida community tested an intergenerational program to help older adults adopt mobile health technology using smartwatches and assessed daily brain health behaviors. Despite challenges with digital literacy, 91% of participants engaged with health surveys delivered via the devices. Social contact was positively linked to physical activity, mental engagement and cognitive well-being. The participants, aged 53-84, successfully used the smartwatches regardless of their health literacy or technological skills, highlighting the potential of such programs in supporting aging in place.