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Support vector machine-based classification of neuroimages in Alzheimer’s disease: direct comparison of FDG-PET, rCBF-SPECT and MRI data acquired from the same individuals

机译：基于支持向量机的阿尔茨海默病神经影像分类：直接比较FDG-pET，rCBF-spECT和从同一个体获得的mRI数据

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Luiz K. Ferreira; Jane M. Rondina; Rodrigo Kubo; Carla R. Ono; Claudia C. Leite; Jerusa Smid; Cassio Bottino; Ricardo Nitrini; Geraldo F. Busatto; Fabio L. Duran; Carlos A. Buchpiguel;
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1. Support vector machine-based classification of neuroimages in Alzheimer’s disease: direct comparison of FDG-PET, rCBF-SPECT and MRI data acquired from the same individuals [J] . Ferreira Luiz K., Rondina Jane M., Kubo Rodrigo, Revista Brasileira de Psiquiatria . 2018,第AHEAD期

机译：基于支持向量机的阿尔茨海默氏病神经图像分类：直接比较从同一人获得的FDG-PET，rCBF-SPECT和MRI数据
2. Support vector machine-based classification of Alzheimer’s disease from whole-brain anatomical MRI [J] . Benoît Magnin, Lilia Mesrob, Serge Kinkingnéhun, Neuroradiology . 2009,第2期

机译：基于全脑解剖MRI的基于支持向量机的阿尔茨海默氏病分类
3. Support vector machine-based classification of Alzheimer's disease from whole-brain anatomical MRI. [J] . Magnin B, Mesrob L, Kinkingnehun S, Neuroradiology . 2009,第2期

机译：基于全脑解剖MRI的基于支持向量机的阿尔茨海默氏病分类。
4. Hybrid CNN-SVM for Alzheimer's Disease Classification from Structural MRI and the Alzheimer's Disease Neuroimaging Initiative(ADNI) [C] . Lan Lin, Baiwen Zhang, Shuicai Wu International Conference on Biomedical Engineering, Machinery and Earth Science . 2018

机译：用于阿尔茨海默病的杂交CNN-SVM从结构MRI和阿尔茨海默病神经影像倡议（ADNI）的疾病分类
5. Deep Learning based Classification of FDG-PET Data for Alzheimer's Disease. [D] . Singh, Shibani. 2017

机译：基于深度学习的阿尔茨海默氏病FDG-PET数据分类。
6. Support vector machine-based classification of neuroimages in Alzheimer’s disease: direct comparison of FDG-PET rCBF-SPECT and MRI data acquired from the same individuals [O] . Luiz K. Ferreira, Jane M. Rondina, Rodrigo Kubo, 2018

机译：基于支持向量机的阿尔茨海默氏病神经图像分类：从相同个体获得的FDG-PETrCBF-SPECT和MRI数据的直接比较
7. Can dimensionality reduction through feature extraction improve classification accuracy compared to whole-brain analysis?: Using high-dimensional neuroimaging data as input for a support vector machine to distinguish alzheimer patients from healthy controls [O] . Broers Thomas 2017

机译：与全脑分析相比，通过特征提取进行降维是否可以提高分类准确性？：使用高维神经影像数据作为支持向量机的输入，以区分阿尔茨海默氏症患者与健康对照

Support vector machine-based classification of neuroimages in Alzheimer’s disease: direct comparison of FDG-PET, rCBF-SPECT and MRI data acquired from the same individuals

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