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

Machine Learning (2046) New Methods (1126) Decision Support for Health Professionals (1515) Tools, Programs and Algorithms (371) AI Language Models in Health Care (190) Methods and New Tools in Mental Health Research (551) Dementia and Cognitive Decline (685)

Published on in Vol 12 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/59396, first published .
A Multivariable Prediction Model for Mild Cognitive Impairment and Dementia: Algorithm Development and Validation

A Multivariable Prediction Model for Mild Cognitive Impairment and Dementia: Algorithm Development and Validation

A Multivariable Prediction Model for Mild Cognitive Impairment and Dementia: Algorithm Development and Validation

Authors of this article:

Sarah Soyeon Oh1 Author Orcid Image ;   Bada Kang2, 3 Author Orcid Image ;   Dahye Hong2, 4 Author Orcid Image ;   Jennifer Ivy Kim2 Author Orcid Image ;   Hyewon Jeong5 Author Orcid Image ;   Jinyeop Song6 Author Orcid Image ;   Minkyu Jeon7 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics

Journals

  1. Yongcharoenchaiyasit K, Arwatchananukul S, Hristov G, Temdee P. Enhanced Multi-Model Machine Learning-Based Dementia Detection Using a Data Enrichment Framework: Leveraging the Blessing of Dimensionality. Bioengineering 2025;12(6):592 View
  2. Oravecz Z, Sliwinski M, Kim S, Williams L, Katz M, Vandekerckhove J. Partially Observable Predictor Models for Identifying Cognitive Markers. Computational Brain & Behavior 2025;8(3):410 View
  3. Dai C, Zhao W, Yang D, Fan G, Meng Q, Yang H, Xie L, Zhang Y, Zha X. Testing the Role of Depression in the Relationship Between Socioeconomic Status and Cognitive Function Among Older Chinese Adults: Findings From the Anhui Healthy Longevity Survey. Alpha Psychiatry 2025;26(5) View