The National Eye Institute (NEI) and National Institutes of Health (NIH) awarded Assistant Professor in the Division of Computational Health Sciences, Mingquan Lin, PhD, a $3.7M five-year grant for his research on Developing Robust Multimodal AI for Primary Open-Angle Glaucoma Prognosis.

Artificial intelligence is quickly moving into medical education. Hospitals and medical schools are exploring how AI can help generate cases, prepare teaching materials, design assessments, and support more personalized learning. But for clinical teachers, being open to AI does not necessarily mean using it in day-to-day teaching.

A new study published in the Chinese Journal of Medical Education Research highlights that gap. Researchers from Peking University First Hospital conducted a questionnaire survey among clinical teachers at a university-affiliated hospital, distributing 359 questionnaires and collecting 335 valid responses and found that teachers reported relatively high willingness to adopt AI-assisted teaching, but much lower levels of actual use. The finding points to a practical challenge for medical education: AI tools may be widely discussed and increasingly accessible, but their integration into clinical teaching still depends on trust, support, and usable implementation pathways.

JMIR Publications released two feature News and Perspectives articles covering health tech research developments, and one investigating the rising use of AI in medical education.

This cohort study of U.S. youths found that year-to-year elevations in self-reported problematic social media use were directly associated with attention-deficit/hyperactivity disorder (ADHD) symptoms during mid-adolescence, particularly among males; reverse associations of ADHD symptoms with later problematic social media use were small in magnitude and sporadic. Screening for hard-to-control social media use, time spent on social media, and attention to sex-specific patterns may be warranted, although the population-based associations may be small.