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This paper introduces MuRAD (Musculoskeletal Radiograph Abnormality Detectiontool), a tool that can help radiologists automate the detection ofabnormalities in musculoskeletal radiographs (bone X-rays). MuRAD utilizes aConvolutional Neural Network (CNN) that can accurately predict whether a boneX-ray is abnormal, and leverages Class Activation Map (CAM) to localize theabnormality in the image. MuRAD achieves an F1 score of 0.822 and a Cohen'skappa of 0.699, which is comparable to the performance of expert radiologists.

Automating Abnormality Detection in Musculoskeletal Radiographs through Deep Learning