Clinical Validation of an AI System for Pneumoconiosis Detection Using Chest X-rays
Journal of Occupational and Environmental Medicine (Lippincott Williams & Wilkins)
Ref: SRC-001-CHL-001
Accessed: 3/26/2026
Summary
Peer-reviewed clinical validation study of eTóraxLaboral evaluating diagnostic performance on 2,300 randomly selected chest radiographs. Reports high sensitivity (LR+ 23, LR- 0.2), 99% accuracy for healthy image detection, slight tendency toward false positives from anatomical superposition, and less frequent false negatives from consolidation misclassification. Authors affiliated with Convicción Digital (Talca) and Mutual de Seguridad (Santiago).
View Harvard reference
Ruiz, E.R., Arellano, C.A., Archila, C.A., Llobet, C., Carrasco, G. and Pinochet, F. (2025) 'Clinical Validation of an AI System for Pneumoconiosis Detection Using Chest X-rays', Journal of Occupational and Environmental Medicine, 67(4), pp. e250–e256. doi: 10.1097/JOM.0000000000003329.