This paper is in the following e-collection/theme issue:

Decision Support for Health Professionals (1569) Artificial Intelligence (2198) Dementia and Cognitive Decline (711) Computer-Aided Diagnosis (261) Voice Phenotyping and Vocal Biomarkers (18) Machine Learning (2130)

Published on in Vol 14 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/80883, first published .
Mild Cognitive Impairment Detection System Based on Unstructured Spontaneous Speech: Longitudinal Dual-Modal Framework

Mild Cognitive Impairment Detection System Based on Unstructured Spontaneous Speech: Longitudinal Dual-Modal Framework

Mild Cognitive Impairment Detection System Based on Unstructured Spontaneous Speech: Longitudinal Dual-Modal Framework

Authors of this article:

Yu-Shan Liao1 Author Orcid Image ;   Thiri Wai2 Author Orcid Image ;   Ting-Yun Liao1 Author Orcid Image ;   Ho-Ling Chang1 Author Orcid Image ;   Yu-Ling Chang3 Author Orcid Image ;   Li-Chen Fu2, 4 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Yu-Shan Liao   1 , MSc ;   Thiri Wai   2 , MSc ;   Ting-Yun Liao   1 , MSc ;   Ho-Ling Chang   1 , MSc ;   Yu-Ling Chang   3 , PhD ;   Li-Chen Fu   2, 4 , MSc, PhD

1 Graduate Institute of Networking and Multimedia, National Taiwan University, Taipei, Taiwan

2 Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan

3 Department of Psychology, National Taiwan University, Taipei, Taiwan

4 Center of Artificial intelligence Research, University of Tsukuba, Tsukuba, Ibaraki, Japan

Corresponding Author:

  • Li-Chen Fu, MSc, PhD
  • Department of Computer Science and Information Engineering
  • National Taiwan University
  • No. 1, Sec 4, Roosevelt Rd
  • Taipei
  • Taiwan
  • Phone: 886 0233663366
  • Email: lichen@ntu.edu.tw