A Correlative Classification Study of Schizophrenic Patients with Results of Clinical Evaluation and Structural Magnetic Resonance Images

Wen Lin Chu, Min Wei Huang, Bo Lin Jian, Chih Yao Hsu, Kuo Sheng Cheng

研究成果: Article同行評審

5 引文 斯高帕斯(Scopus)

摘要

Patients with schizophrenia suffer from symptoms such as hallucination and delusion. There are currently a number of publications that discuss the treatment, diagnosis, prognosis, and damage in schizophrenia. This study utilized joint independent component analysis to process the images of GMV and WMV and incorporated the Wisconsin card sorting test (WCST) and the positive and negative syndrome scale (PANSS) to examine the correlation of obtained brain characteristics. We also used PANSS score to classify schizophrenic patients into acute and subacute cases, to analyze the brain structure differences. Finally, we used brain structure images and the error rate of the WCST as eigenvalues in support vector machine learning and classification. The results of this study showed that the frontal and temporal lobes of a normal brain are more apparent than those of a schizophrenia brain. The highest level of classification recognition reached 91.575%, indicating that the WCST error rate and characteristic changes in brain structure volume can be used to effectively distinguish schizophrenia and normal brains. Similarly, this result confirmed that the WCST and brain structure volume are correlated with the differences between schizophrenia and normal participants.

原文English
文章編號7849526
期刊Behavioural Neurology
2016
DOIs
出版狀態Published - 2016

All Science Journal Classification (ASJC) codes

  • Neuropsychology and Physiological Psychology
  • Neurology
  • Clinical Neurology

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