MLD3/Deep-Learning-Applied-to-Chest-X-rays-Exploiting-and-Preventing-Shortcuts
[MLHC 2020] Deep Learning Applied to Chest X-Rays: Exploiting and Preventing Shortcuts (Jabbour, Fouhey, Kazerooni, Sjoding, Wiens). https://arxiv.org/abs/2009.10132
This project helps medical researchers and clinicians analyze chest X-ray images to identify specific conditions like pneumonia or congestive heart failure. It takes raw chest X-ray images and patient metadata as input and provides diagnostic predictions, helping to understand and prevent 'shortcuts' or biases in how AI models interpret these images. Researchers studying medical image diagnostics would find this useful.
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Use this if you are a medical researcher or data scientist working with chest X-ray datasets (like MIMIC-CXR or CheXpert) and want to develop or evaluate diagnostic AI models, especially to identify and mitigate biases.
Not ideal if you are a clinician looking for a ready-to-use diagnostic tool for patient care, as this project focuses on research and model development rather than direct clinical application.
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Oct 04, 2022
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