Our project focuses on elucidating the unique visual patterns of abusive (non-accidental) child injury and developing an application to identify them automatically.
Dr. Talia M. Schwartz-Tayri, Ph.D
Head and founder, the AI for SW lab
Spitzer Department of Social Work at Ben Gurion University of the Negev
Dr. Dan Vilenchik, Ph.D
School of Electrical and Computer Engineering, the Faculty of Engineering Sciences at Ben Gurion University of the Negev
Dr. Michal S. Maimon, M.D.
Head of pediatric ER unit, Soroka University Medical Center
“Beit Lynn”, Child Advocacy Center
Dr. Ricardo Nachman, M.D.
National Center of Forensic Medicine in Israel
Child and Elderly Abuse and Neglect Prevention Committee
Dr. Galit Fuhrmann Alpert, Ph.D
Data4Good Lab
Software and Information Systems Engineering Department
Ben Gurion University of the Negev
Providing children with a safe environment is one of the most important values of modern societies. The innovation of this study lies in the multidisciplinarity of our team, as it harnesses the cumulative knowledge and expertise of researchers in social welfare, pediatrics, forensic medicine, and data science to develop an AI tool that can effectively support medical staff's decision-making in cases of suspected non-accidental child injuries. Our initial project focuses on elucidating the unique visual patterns of abusive (non-accidental) burns and develop an application to identify them automatically. We will apply our technology to identify the source of additional types of child injuries and develop an automatic system to support medical staff diagnosis of abusive (non-accidental) injuries.
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