Predicting the cognitive impairment with multimodal ophthalmic imaging and artificial neural network for community screening.

Journal: The British journal of ophthalmology
Published Date:

Abstract

BACKGROUND/AIMS: To investigate the comprehensive prediction ability for cognitive impairment in a general elder population using the combination of the multimodal ophthalmic imaging and artificial neural networks.

Authors

  • Zi Jin
    National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou, China; National Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, China.
  • Xuhui Chen
    Satellite Application Center for Ecology and Environment, Beijing 100094, China.
  • Chunxia Jiang
    Department of Ophthalmology, Peking University Shenzhen Hospital, Shenzhen, China.
  • Ximeng Feng
    Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China.
  • Da Zou
    Department of Biomedical Engineering, Peking University Shenzhen Graduate School, Shenzhen, China.
  • Yanye Lu
    Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg, Martensstr. 3, 91058, Erlangen, Germany. yanye.lu@fau.de.
  • Jinying Li
    Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, School of Environment and Energy, South China University of Technology, Guangzhou Higher Education Mega Center, Guangzhou, 510006, China.
  • Qiushi Ren
    Department of Biomedical Engineering, Peking University, 100871, Beijing, China.
  • Chuanqing Zhou
    Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen, China.