Abstract #5474

A support vector machine-based method to identify non-neuropsychiatric systemic lupus erythematosus with Regional Homogeneity

Xiangliang Tan¹, Zhuqing Long², Yingjie Mei³, Wenjun Qiao¹, Kai Han⁴, and Yikai Xu¹

¹Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China, ²Medical apparatus and equipment deployment, Nanfang Hospital, Southern Medical University, Guangzhou, China, ³Philips Healthcare, Guangzhou, China, ⁴Department of Dermatology, Nanfang Hospital, Southern Medical University, Guangzhou, China

Previous studies found that changes in brain function happened in default mode network beforeNeuropsychiatric involvement (NPSLE) development by using resting-state functional magnetic resonance imaging (rs-fMRI), highlighting the need for early evaluation and intervention in SLE patients. In this study, we proposed a valid Support Vector Machine (SVM) -based method to identify non-NPSLE using regional homogeneity (ReHo). The results demonstrate that ReHo parameter is an effective classification feature for the SVM-based method to identify SLE patients from healthy subjects.

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