Mild cognitive impairment prediction based on multi-stream convolutional neural networks.

Journal: BMC bioinformatics
Published Date:

Abstract

BACKGROUND: Mild cognitive impairment (MCI) is the transition stage between the cognitive decline expected in normal aging and more severe cognitive decline such as dementia. The early diagnosis of MCI plays an important role in human healthcare. Current methods of MCI detection include cognitive tests to screen for executive function impairments, possibly followed by neuroimaging tests. However, these methods are expensive and time-consuming. Several studies have demonstrated that MCI and dementia can be detected by machine learning technologies from different modality data. This study proposes a multi-stream convolutional neural network (MCNN) model to predict MCI from face videos.

Authors

  • Chien-Cheng Lee
  • Hong-Han Hank Chau
    Department of Electrical Engineering, Yuan Ze University, Taoyuan, 320, Taiwan.
  • Hsiao-Lun Wang
    Department of Electrical Engineering, Yuan Ze University, Taoyuan, 320, Taiwan.
  • Yi-Fang Chuang
    Institute of Public Health, College of Medicine, National Yang Ming Chiao Tung University, Taipei, 112, Taiwan.
  • Yawgeng Chau
    Department of Electrical Engineering, Yuan Ze University, Taoyuan, 320, Taiwan.