dstrick17/DacNet
Reproducing and Improving CheXNet: Deep Learning for Chest X-ray Disease Classification
This project helps radiologists, medical researchers, or healthcare practitioners quickly identify up to 14 common thoracic diseases from chest X-ray images. You input a chest X-ray image, and it outputs a list of potential diseases with their likelihood. It's designed for medical professionals who analyze diagnostic imaging.
Use this if you need a deep learning model to automatically detect multiple diseases from chest X-rays, especially if you want a robust solution for imbalanced disease prevalence.
Not ideal if you require a solution verified with a fully expert-labeled test set or if you are not comfortable with basic data path configuration.
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17
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11
Language
Jupyter Notebook
License
MIT
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Last pushed
Feb 24, 2026
Commits (30d)
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