Enhancing identification performance of cognitive impairment high-risk based on a semi-supervised learning method.

Journal: Journal of biomedical informatics
Published Date:

Abstract

BACKGROUND: Cognitive assessment plays a pivotal role in the early detection of cognitive impairment, particularly in the prevention and management of cognitive diseases such as Alzheimer's and Lewy body dementia. Large-scale screening relies heavily on cognitive assessment scales as primary tools, with some low sensitivity and others expensive. Despite significant progress in machine learning for cognitive function assessment, its application in this particular screening domain remains underexplored, often requiring labor-intensive expert annotations.

Authors

  • Sumei Yao
    Center for Studies of Information Resources, Wuhan University, Wuhan, China; Big Data Research Institute, Wuhan University, Wuhan, China.
  • Yan Zhang
    Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, 110032, China.
  • Jing Chen
    Department of Vascular Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, P.R. China.
  • Quan Lu
    School of Information Management, Wuhan University, Wuhan, China.
  • Zhiguang Zhao
    Department of Elderly Health Management, Shenzhen Center for Chronic Disease Control, No.2021, Buxin Road, Shenzhen, Guangdong, 518020, China. 1498384005@qq.com.