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Abstract #3511

Novel machine learning method for clinically significant cortical lesion detection in multiple sclerosis

Eve L Kazarian1, Mariam S Aboian1, and John D Port2
1Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, United States, 2Department of Radiology, Mayo Clinic, Rochester, MN, United States

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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