Research

Newly patented AI technology helps get bruise detection tools into the hands of clinicians, law enforcement, and researchers

A study by Panagiota Kitsantas and colleagues reveals patterns of treatment delays for youth with cannabis use disorder.

A new paper from George Mason University outlines how health administration programs can better prepare students to support health care workers.

With funding from the National Institute on Aging, George Mason health economist Jeah Jung will evaluate how Medicare Advantage’s new non-medical benefits like food and transportation impact health care use and patient outcomes.

Research by George Mason digital technology expert Y. Alicia Hong and obesity expert Larry Cheskin, big data expert Hong Xue, and MS Health Informatics graduate Jo-Vivian Yu found that the eating environments of college students affect their food intake.

WECARE 2.0, a digitally delivered health promotion program for Chinese American dementia caregivers, is easy to use for all literacy levels and increases social supports. An innovative assessment by PhD student Kang Shen highlights that self-report feedback and website activity are crucial for understanding the delivery of a digital intervention.

Digital health researcher Y. Alicia Hong’s WECARE intervention will invigorate resilience in family caregivers of individuals with dementia

Y. Alicia Hong, a digital behavioral health interventionist, will support older adults in honing their digital technology skills. The program, through an interdisciplinary partnership, will pair youth and older adults to practice real-life AI scenarios.

An interdisciplinary George Mason University research team is breaking new ground in using artificial intelligence to develop a mobile app to accurately capture and document bruises of victims of interpersonal violence.

Researchers Farrokh Alemi and Kevin Lybarger receive George Mason University’s first Patient-Centered Outcomes Research Institute (PCORI) award to develop innovative AI technology, including large language models, for improving antidepressant recommendations.