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This paper proposes a novel multimodal DL architecture incorporating medicalimages and eye-tracking data for abnormality detection in chest x-rays. Ourresults show that applying eye gaze data directly into DL architectures doesnot show superior predictive performance in abnormality detection chest X-rays.These results support other works in the literature and suggest thathuman-generated data, such as eye gaze, needs a more thorough investigationbefore being applied to DL architectures.

Integrating Eye-Gaze Data into CXR DL Approaches: A Preliminary study