An open-source AI model using chest x-rays accurately predicts respiratory mortality in COPD patients, outperforming standard clinical risk grading.
Key Details
- 1CXR-Lung-Risk AI analyzed 4,226 chest x-rays from patients with mild to severe COPD.
- 2Study showed a 16% increase in respiratory mortality risk per five-year rise in AI risk score, after adjusting for clinical risk factors.
- 3AI model outperformed the GOLD grading system in predicting 10-year respiratory mortality (AUC: 0.76 vs 0.61, p < 0.001).
- 4Pulmonary function decreased as AI scores increased (p < 0.001).
- 5Model was tested in an external Asian population, broadening prior validation.
Why It Matters
This research demonstrates real-world value for deep learning in extracting prognostic biomarkers from standard chest radiographs, potentially aiding clinicians in risk stratification and management of COPD beyond conventional methods.
Source
AuntMinnie
Related News
•AuntMinnie
Debate at RSNA 2025 Examines If AI Is Ready for Autonomous Chest X-ray Reads
Experts at RSNA 2025 debated whether AI is ready for fully autonomous interpretation of chest x-rays, concluding that while technical progress is evident, significant challenges remain.
•AuntMinnie
Study: Patients Prefer AI in Radiology as Assistive, Not Standalone Tool
Survey finds patients support AI-assisted radiology but not AI-only interpretations.
•AuntMinnie
AI-Enhanced MRI Boosts Return-to-Play Predictions for Athlete Muscle Injuries
Adding AI to MRI-based classification systems improves return-to-play predictions for professional athletes with muscle injuries.