
Researchers developed an AI model that can accurately detect fatty liver disease from routine chest X-rays.
Key Details
- 1The AI model was created by Osaka Metropolitan University researchers.
- 2It was trained and validated with 6,599 chest X-ray images from 4,414 patients.
- 3Model performance was strong, with AUC between 0.82 and 0.83.
- 4Chest X-rays are less costly and more commonly performed than ultrasounds, CTs, or MRIs currently used for liver diagnosis.
- 5Results were published in Radiology Cardiothoracic Imaging on June 20, 2025.
Why It Matters
This approach could enable earlier and more widespread detection of fatty liver disease using existing chest X-rays, reducing the need for more expensive or specialized imaging modalities. It demonstrates the potential for AI to repurpose common imaging studies for new clinical insights in radiology.

Source
EurekAlert
Related News

•EurekAlert
Study Warns: AI Alone Is Not Enough in Critical Healthcare Decisions
Evaluating both AI algorithms and human users is key for safe adoption in high-stakes healthcare settings, according to an Ohio State study.

•EurekAlert
AI Dramatically Improves Prediction of Delivery Timing from Ultrasound Images
Ultrasound AI's study validates advanced AI for predicting delivery timing using standard ultrasound images.

•EurekAlert
AI-Assisted Colonoscopies May Reduce Clinicians’ Detection Skills, Study Finds
Routine use of AI in colonoscopies linked to decreased skill in adenoma detection by clinicians without AI assistance.