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Pattern analysis for the neuroimaging based diagnosis of schizophrenia

机译：基于神经影像的精神分裂症诊断的模式分析

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Accurate diagnosis at an early stage of schizophrenia, a chronic and severe mental illness that affects people's thoughts, feelings, and behavior, has a critical importance for the initiation of the treatment and monitoring of the disease. In this study, a pattern analysis study is performed for the diagnosis of schizophrenia using structural magnetic resonance (MR) images. Morphometric features like volumes and thickness of the anatomical structures of the brain that reveal the disease-related patterns are used to discriminate between schizophrenia patients and healthy controls. Morphometric brain features that are obtained from the MR images of 150 subjects are analyzed with support vector machines (SVM) trained with 5-fold cross validation. Results obtained from the study showed that using SVM together with morphometric brain features could be a successful complementary method for the early clinical diagnosis of schizophrenia.
机译：在精神分裂症的早期进行准确诊断，精神分裂症是一种慢性和严重的精神疾病，会影响人们的思想，感觉和行为，对于启动该疾病的治疗和监测至关重要。在这项研究中，进行了模式分析研究，以使用结构磁共振（MR）图像诊断精神分裂症。揭示疾病相关模式的形态特征（如大脑解剖结构的体积和厚度）可用于区分精神分裂症患者和健康对照。从150名受试者的MR图像中获得的形态学大脑特征用经过5倍交叉验证训练的支持向量机（SVM）进行分析。从研究中获得的结果表明，将SVM与形态计量学的脑部特征结合使用可能是对精神分裂症的早期临床诊断的成功补充方法。

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