Researchers introduce CoRaX, an AI system that uses eye gaze and radiology report data to address perceptual errors in chest x-ray readings.
Key Details
- 1CoRaX combines eye gaze data, chest x-ray images, and radiology reports for collaborative error detection.
- 2Developed by the University of Houston, the system acts as a 'virtual second reader' and provides targeted diagnostic recommendations.
- 3Evaluation on simulated datasets showed CoRaX corrected 21.3% and 34.6% of perceptual errors, depending on the scenario.
- 4Diagnostic aid was provided in 85.7% and 78.4% of interactions in two different datasets.
- 5The system performed particularly well for missed cases of cardiomegaly.
- 6Future directions include real-world validation and possible integration of more advanced classifiers.
Why It Matters

Source
AuntMinnie
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