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

AI in Older Adult Care (32) Dementia and Cognitive Decline (586) Machine Learning (1730) mHealth for Screening (257) Diagnostic Tools in Mental Health (279)

Published on in Vol 7 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/55126, first published .
Detection of Mild Cognitive Impairment From Non-Semantic, Acoustic Voice Features: The Framingham Heart Study

Detection of Mild Cognitive Impairment From Non-Semantic, Acoustic Voice Features: The Framingham Heart Study

Detection of Mild Cognitive Impairment From Non-Semantic, Acoustic Voice Features: The Framingham Heart Study

Authors of this article:

Huitong Ding1, 2 Author Orcid Image ;   Adrian Lister3 Author Orcid Image ;   Cody Karjadi1, 2 Author Orcid Image ;   Rhoda Au1, 2, 4, 5 Author Orcid Image ;   Honghuang Lin6 Author Orcid Image ;   Brian Bischoff3 Author Orcid Image ;   Phillip H Hwang1, 2, 4 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics

Journals

  1. Sung S, Hong S, Kim J, Kang D, Park H, Kim S. Cognitive Impairment Classification Prediction Model Using Voice Signal Analysis. Electronics 2024;13(18):3644 View
  2. Ahangaran M, Dawalatabad N, Karjadi C, Glass J, Au R, Kolachalama V. Obfuscation via pitch‐shifting for balancing privacy and diagnostic utility in voice‐based cognitive assessment. Alzheimer's & Dementia 2025;21(3) View
  3. LEE S, YOUN Y, YUN G, LEE H, KIM S, KIM I, JEONG H. Role of Voice Signal Analysis in Screening for Cognitive Impairment: A Study on Community-dwelling Older Adults. Korean Journal of Clinical Laboratory Science 2025;57(1):48 View