基于多尺度残差神经网络的阿尔茨海默病诊断分类
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刘振丙,方旭升,杨辉华,蓝如师
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The diagnosis of Alzheimer's disease classification based on multi-scale residual neutral network
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Zhenbing LIU,Xusheng FANG,Huihua YANG,Rushi LAN
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表3 每一种模型的准确率
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Table 3 The accuracy performance for each model
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% | 模型 | AD vs NC | AD vs MCI | MCI vs NC | AD vs NC vs MCI | BA+Resnet | 96.51 | 93.11 | 84.93 | 82.36 | ST+Resnet | 97.45 | 94.28 | 85.55 | 83.51 | BA+MSResnet | 98.32 | 95.15 | 86.70 | 83.87 | ST+SVM | 90.16 | 88.19 | 80.26 | 75.26 | ST+ELM | 91.35 | 86.46 | 81.79 | 77.07 | ST+Alexnet | 93.49 | 91.92 | 83.04 | 80.30 | ST+VGG16 | 95.83 | 93.76 | 84.16 | 81.25 | ST+GoogLenet | 97.86 | 94.49 | 86.05 | 83.57 | ST+MSResnet | 99.41 | 97.35 | 87.75 | 85.53 |
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