AI-driven multimodal precision diagnosis and progression prediction of Alzheimer’s disease: Data fusion mechanisms, clinical applications, and research trends (2017–2024)
Research on multimodal AI for AD has gained global attention and remains a key direction for diagnostic innovation. By synthesizing bibliometric insights with structured analyses of modalities and fusion strategies, this study offers a systematic understanding of current progress and provides valuable guidance for future methodological and translational research.
Authors
- Wenhui Zhou (ORCID: https://orcid.org/0000-0003-2178-3959)
- Wu Yz
- He Huang (ORCID: https://orcid.org/0000-0002-2052-718X)
- X Li
- Hong Liu (ORCID: https://orcid.org/0000-0003-3611-7131)
- Zhichang Zhang
- Yanhua Wang
Institutions
- Shenyang Medical College (CN)
- Educational Department of Liaoning Province (CN)
- Shenyang Center for Disease Control and Prevention (CN)
- Shenyang University (CN)
Publication Details
- Journal
- Digital Health
- Published
- 2026-02-01
- DOI
- https://doi.org/10.1177/20552076251412649
- Primary Topic
- Dementia and Cognitive Impairment Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00