ukaukaaaa/GazeGNN
Official Code for GazeGNN: A Gaze-guided Graph Neural Network for Chest X-ray Classification [WACV 2024]
This tool helps radiologists and medical professionals quickly and accurately classify chest X-ray images for conditions like congestive heart failure and pneumonia. By integrating raw eye-gaze data from radiologists' viewing patterns directly with the X-ray image, it provides real-time disease classifications. The input is a chest X-ray image and the radiologist's eye-gaze data, and the output is a disease classification.
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Use this if you are a radiologist or medical professional seeking to leverage your real-time eye-gaze patterns to enhance the accuracy and speed of chest X-ray image diagnoses.
Not ideal if you do not have access to real-time eye-gaze tracking data or are looking for a solution that does not incorporate human visual attention patterns.
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Language
Python
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Last pushed
Aug 25, 2023
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