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

Digital Health Reviews (3810) Clinical Information and Decision Making (3850) Decision Support for Health Professionals (2311) Dementia and Cognitive Decline (908) Diagnostic Tools in Mental Health (453) Machine Learning (3303) Artificial Intelligence (4936)

Published on in Vol 28 (2026)

This is a member publication of University of Bristol (Jisc)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/85414, first published .
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Multimodal AI for Alzheimer Disease Diagnosis: Systematic Review of Datasets, Models, and Modalities

Multimodal AI for Alzheimer Disease Diagnosis: Systematic Review of Datasets, Models, and Modalities

Authors of this article:

Ziwen Yu1 Author Orcid Image ;   Anthony Mulholland1 Author Orcid Image ;   Tianyan Huang2 Author Orcid Image ;   Qiang Liu1 Author Orcid Image
Article Authors Cited by (8) Tweetations (1) Metrics

Journals

  1. Rusek M, Pitucha M. From Genes to Imaging Phenotypes: Radiomics and Machine Learning as Tools to Decode Molecular Pathways in Alzheimer’s Disease. Genes 2026;17(6):672 View
  2. Emdad F, Rahman M, Nabil H, Rayed E, Ovi P, Emdad E, Rahman M, Talukdar M, Hossain M. A Generalized Responsible AI Framework for Trustworthy Clinical Prediction: Explainability, Fairness, Performance, and Uncertainty in Alzheimer’s Disease Modeling. Healthcare 2026;14(12):1721 View
  3. Kumbhar S, Bhinge S, Bhatia M. TEMPORARY REMOVAL: Analytical and Computational Challenges in AI-Driven Biomarker Assays for Neurodegenerative Diseases: Current Limitations, Validation Strategies, and Future Perspectives. Advances in Biomarker Sciences and Technology 2026 View
  4. Fakoya J, Falayi C, Ajinaja M. <p>Predicting Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer Using Multi-Omics and Machine Learning</p>. Cureus Journal of Computer Science 2026 View
  5. Al-Naami B, Almomani L, Al-Naimat F, Al-Hinnawi A. Beyond AT(N): Integrating Neuroimaging, Fluid Biomarkers, and Artificial Intelligence for Alzheimer’s Disease Diagnosis—A Review. BioMedInformatics 2026;6(5):65 View
  6. Ruiz-Vanoye J, Trejo Macotela F, Diaz-Parra O, Sossa‑Azuela J, Fuentes-Penna A, Simancas-Acevedo E. Contemporary Classifications of Alzheimer’s Disease: A Critical Review of Clinical, Biological, Neuropathological, Functional, Phenotypic and Neuroinformational Frameworks. International Journal of Combinatorial Optimization Problems and Informatics 2026;18(1):281 View
  7. Abu-Alsaad H, Alzubaydi N, Mutashar H. An Explainable Multimodal AI Software Framework for 36-Month MCI-to-Alzheimer’s Disease Progression Prediction: A Methodological Evaluation. Big Data and Cognitive Computing 2026;10(10):326 View
  8. Shateri A, Rezaei S. Multimodal artificial intelligence in Alzheimer’s disease: integrating biomarkers toward precision diagnosis and clinical translation. Romanian Journal of Neurology 2026;25(3):315 View