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

Tools, Programs and Algorithms (402) Machine Learning (2199) Decision Support for Health Professionals (1612) Dementia and Cognitive Decline (732)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/60250, first published .
Retracted: A Dynamic Adaptive Ensemble Learning Framework for Noninvasive Mild Cognitive Impairment Detection: Development and Validation Study

Retracted: A Dynamic Adaptive Ensemble Learning Framework for Noninvasive Mild Cognitive Impairment Detection: Development and Validation Study

Retracted: A Dynamic Adaptive Ensemble Learning Framework for Noninvasive Mild Cognitive Impairment Detection: Development and Validation Study

Authors of this article:

Aoyu Li1 Author Orcid Image ;   Jingwen Li2 Author Orcid Image ;   Yishan Hu3 Author Orcid Image ;   Yan Geng4 Author Orcid Image ;   Yan Qiang5 Author Orcid Image ;   Juanjuan Zhao1, 3 Author Orcid Image
Article Authors Cited by (4) Tweetations Metrics

Journals

  1. Lee G, Geem Z. Harmony Search Algorithm with Two Problem-Specific Operators for Solving Nonogram Puzzle. Mathematics 2025;13(9):1470 View
  2. . Expression of Concern: A Dynamic Adaptive Ensemble Learning Framework for Noninvasive Mild Cognitive Impairment Detection: Development and Validation Study. JMIR Medical Informatics 2025;13 View
  3. Sirshar M, Matloob I, Tayyabah A, Syed F, Ashraf A, Alfraihi H. MCI detection from handwritten drawing test using residual vision transformer. Scientific Reports 2026 View
  4. Chong Y, Duan C, Xu X, Li Z, Zhang H, Gong J, Wu Q, Xia L, Zhang P, Xia W. fNIRS-based early identification of mild cognitive impairment: a large-scale multi-paradigm study with ensemble machine learning models. Frontiers in Neurology 2026;17 View