Intimate partner violence refers to abuse from current or former partners and can lead to severe injuries, chronic pain, and mental health disorders. According to a European Commission report, 18 percent of women who had ever had a partner said they experienced physical or sexual violence by their partner in 2021. Current screening for domestic abuse in hospitals usually relies on doctors asking patients questions about their safety at home, but many victims do not disclose abuse due to fear, stigma, or safety concerns, leading to cases often going undetected.
Researchers in the United States trained a machine learning model using data collected during regular hospital visits. The research team used records from nearly 850 women who had experienced intimate partner violence and more than 5,200 patients of similar age in a control group to build three different AI systems. The first system analysed structured hospital data such as age and medical history, while the second system looked at written medical notes. The third system combined both types of information. All three models performed strongly, but the combined system proved the most accurate, correctly identifying risk in 88 percent of cases. The tool was also able to flag potential abuse more than three years before many patients later entered hospital-based domestic abuse intervention programmes.
Researchers say that the technology is designed to support clinicians rather than replace their judgment. The technology does not diagnose abuse or force patients to disclose information; instead, it provides a signal that may help doctors approach the topic carefully and offer support if needed. It remains unknown when the AI tool will be implemented in hospitals or what specific ethical guidelines will govern its use in clinical settings.