ilias-ant/x-ray-abnormality-detection
An attempt at the Bone X-Ray Deep Learning Competition (Stanford ML Group).
This project helps radiologists and medical practitioners quickly identify abnormalities in upper extremity X-ray images. You input one or more X-ray images from a patient's study, and it outputs a 'normal' or 'abnormal' classification for the study. This is designed for healthcare professionals who need to screen musculoskeletal radiographs efficiently.
No commits in the last 6 months.
Use this if you need an automated tool to assist in the initial screening of upper extremity X-ray images for potential abnormalities.
Not ideal if you require a definitive diagnosis or a tool for detecting very subtle, rare conditions not well-represented in general datasets.
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MIT
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Last pushed
Apr 09, 2022
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