Feature Selection Based on Iterative Canonical Correlation Analysis for Automatic Diagnosis of Parkinson's Disease.

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第一作者： Luyan,Liu

第一单位： School of Biomedical Engineering, Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, China.

作者： Luyan,Liu ^[1] ; Qian,Wang ^[1] ; Ehsan,Adeli ^[2] ; Lichi,Zhang ^[1] ; Han,Zhang ^[2] ; Dinggang,Shen ^[2]

作者单位： School of Biomedical Engineering, Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, China. ^[1] Department of Radiology BRIC, University of North Carolina at Chapel Hill, Chapel Hill, USA. ^[2]

主题词算法(Algorithms);脑(Brain);人类(Humans);磁共振成像(Magnetic Resonance Imaging);帕金森病(Parkinson Disease);结果可重复性(Reproducibility of Results);敏感性与特异性(Sensitivity and Specificity)

DOI 10.1007/978-3-319-46723-8_1

PMID 28593202

发布时间 2024-03-26

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Medical image computing and computer-assisted intervention

2016年9901卷

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Feature Selection Based on Iterative Canonical Correlation Analysis for Automatic Diagnosis of Parkinson's Disease.

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Feature Selection Based on Iterative Canonical Correlation Analysis for Automatic Diagnosis of Parkinson's Disease.

Medical image computing and computer-assisted intervention

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