Mass General Brigham researchers developed AI models that use EMR, including radiology data, to predict risk for intimate partner violence (IPV) years before patients seek care.
Key Details
- 1AI pipeline trained on 673 IPV cases and 4,169 controls using EMR data from 2017-2022.
- 2Models included structured data, unstructured clinical notes, and radiology/emergency department reports.
- 3The fusion 'Holistic AI in Medicine (HAIM)' model achieved the highest accuracy (88%).
- 4Fusion model could predict 80.5% of IPV cases on average 3.7 years before patients sought care.
- 5Validated on two external datasets with similarly high accuracy.
- 6Research led by Mass General Brigham radiologist; funded by NIBIB and NIH.
Why It Matters
Early detection of IPV could allow healthcare providers to intervene and prevent serious harm. Demonstrates the unique value of including radiology and unstructured EMR data in risk prediction models for vulnerable patient groups.
Source
EurekAlert
Related News
•EurekAlert
FDA Approves Johns Hopkins AI Tool for Early Sepsis Detection
FDA clears an AI-driven system developed by Johns Hopkins to detect sepsis up to 48 hours earlier and reduce mortality rates.
•EurekAlert
New AI Vision-Language Model Enhances Chest CT Diagnostics
Researchers developed an interpretable AI model that uses visual question answering to generate detailed diagnostic findings from chest CT scans, aimed at improving lung cancer diagnosis.
•EurekAlert
Optical AI Chip Boosts Real-Time Dry Eye Gland Diagnosis Accuracy
A new metasurface spectral AI chip enables rapid, accurate diagnosis of meibomian gland dysfunction (MGD) from tissue samples, achieving 96.22% accuracy.