A novel tree-based machine learning model was applied to head MR imaging scans from multiple sclerosis (MS) patients in order to detect cortical gray matter lesions. Cortical lesions are strong indicators of MS disability yet are not easily visualized in clinical practice. The model was useful for accurately detecting cortical lesion presence (AUC of 0.78 ± 0.02).
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