Intelligent prediction of Alzheimer’s disease via improved multifeature squeeze-and-excitation-dilated residual network
Zengbei Yuan,
Xinlin Li,
Zezhou Hao
et al.
Abstract:This study aimed to address the issue of larger prediction errors existing in intelligent predictive tasks related to Alzheimer’s disease (AD). A cohort of 487 enrolled participants was categorized into three groups: normal control (138 individuals), mild cognitive impairment (238 patients), and AD (111 patients) in this study. An improved multifeature squeeze-and-excitation-dilated residual network (MFSE-DRN) was proposed for two important AD predictions: clinical scores and conversion probability. The model … Show more
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