机译:通过结合多种措施改善阿尔茨海默氏病的分类
School of Information Science and Engineering, Central South University, Changsha, China;
School of Information Science and Engineering, Central South University, Changsha, China;
School of Computer Science and Information Technology, Guangxi Normal University, Guilin, China;
School of Information Science and Engineering, Lanzhou University, Lanzhou, China;
Division of Biomedical Engineering and Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, SK, Canada;
Department of Computer Science, Georgia State University, Atlanta, GA;
Magnetic resonance imaging; Feature extraction; Computed tomography; Dementia; Kernel; Surface reconstruction;
机译:结合多种解剖MRI测量可改善阿尔茨海默氏病的分类
机译:随机森林特征选择,融合与集合策略:结合多种形态MRI措施,歧视Healhy老年,MCI,CMCI和Alzheimer病患者:来自阿尔茨海默病神经影像倡议(ADNI)数据库
机译:结合MRI和CSF措施对阿尔茨海默氏病进行分类并预测轻度认知障碍转化
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
机译:通过使用置信度度量组合分类器来提高分类准确性。
机译:结合多种解剖MRI测量可改善阿尔茨海默氏病的分类
机译:结合多重解剖MRI测量改善了阿尔茨海默病的分类