By Jessica Kent
Health IT Analytics
An explainable artificial intelligence platform that analyzes data captured during in-person consultations may enhance diagnosis and treatment of adverse childhood experiences (ACEs), according to a study published in JMIR – Medical Informatics.
ACEs are negative events and processes that an individual might encounter during childhood or adolescence. These events have been proven to be linked to increased risk of a range of negative health outcomes and conditions in adulthood.
Because the social determinants of health have a similarly profound impact on physical well-being, researchers noted that many studies have focused on studying the links between social determinants of health, ACEs, and health outcomes.
However, there are few intelligent tools available to assist in the real-time screening of patients and assess the connection between ACEs and social determinants of health, which could help guide patients and families to available resources.
The research team worked to develop an AI platform that could help providers diagnose ACEs in the early stages.
“Current treatment options are long, complex, costly, and most of the time a non-transparent process,” said Arash Shaban-Nejad, PhD, MPH, an assistant professor at the Center for Biomedical Informatics in the Department of Pediatrics at the University of Tennessee Health Science Center.
“We aim not only to assist healthcare practitioners in extracting, processing, and analyzing the information, but also to inform and empower patients to actively participate in their own healthcare decision-making process in close cooperation with medical and healthcare professionals.”
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