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An AI tool developed by Mass General Brigham accurately predicts intimate partner violence risk years before diagnosis using medical records.
Researchers at Mass General Brigham, funded by the NIH, developed an AI tool using machine learning to predict intimate partner violence (IPV) risk by analyzing electronic medical records.
The fusion model, HAIM, achieved 88% accuracy and identified 80.5% of IPV cases up to 3.7 years before clinical presentation, using both structured and unstructured data.
It detected risk factors like mental health issues, frequent ER visits, and social deprivation, while preventive care was linked to lower risk.
The tool is not for diagnosis but aims to support early, proactive screening, especially since many victims don’t disclose abuse.
Limitations include potential false negatives and the need for more diverse data.
The approach shows promise for improving early intervention and health outcomes.
Una herramienta de IA desarrollada por Mass General Brigham predice con precisión el riesgo de violencia de pareja íntima años antes del diagnóstico utilizando registros médicos.