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
MD Anderson Unveils New AI Genomics Insights and Therapeutic Advances
MD Anderson reports breakthroughs in cancer therapeutics and provides critical insights into AI models for genomic analysis.
•EurekAlert
UCLA Researchers Present AI, Blood Biomarker Advances at SABCS 2025
UCLA Health researchers unveil major advances in breast cancer AI pathology, liquid biopsy, and biomarker strategies at the 2025 SABCS.
•EurekAlert
SH17 Dataset Boosts AI Detection of PPE for Worker Safety
University of Windsor researchers released SH17, a 8,099-image open dataset for AI-driven detection of personal protective equipment (PPE) in manufacturing settings.