ukaukaaaa/GazeGNN

Official Code for GazeGNN: A Gaze-guided Graph Neural Network for Chest X-ray Classification [WACV 2024]

25
/ 100
Experimental

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.

No commits in the last 6 months.

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.

radiology medical-imaging diagnostic-imaging chest-xray-analysis disease-classification
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 8 / 25
Community 11 / 25

How are scores calculated?

Stars

21

Forks

3

Language

Python

License

Last pushed

Aug 25, 2023

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/ukaukaaaa/GazeGNN"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.