Multimodal Approaches for Alzheimer’s Detection Using Patients’ Speech and Transcript
Integrity signals
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Cai et al. achieved accuracy 0.8484 ± 0.0544 on Dementia-Bank Pit using GNN text features and WavLM voice features.
“| Cai et al. [82] | GNN (text features) WavLM (voice features) | Speech, text | Dementia- Bank Pit | Accuracy: 0.8484 ± 0.0544 |”
From A Comprehensive Review on Synergy of Multi-Modal Data and AI Technologies in Medical Diagnosis (2024) · cites this paper as [82]
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References 28 · Cited by 22
- Authors
- Cai, H., Huang, X., Liu, Z., Liao, W., Dai, H., Wu, Z., Zhu, D., Ren, H., Li, Q., Liu, T., & Li, X.
- Affiliations
- South China University of Technology (CN)
- University of Georgia (US)
- The University of Texas at Arlington (US)
- Massachusetts General Hospital (US)
- Corresponding author
- Li, Xiang
- ORCID
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Nature Switzerland
- Published
- 2023
- Pages
- 395-406
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W4386639948
- Cited by
- 22
- References
- 28
- Citations by year
- 2026: 6 · 2025: 7 · 2024: 9
- FWCI
- 12.96
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- Locations
- Lecture notes in computer science (publishedVersion)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Physical Sciences › Computer Science › Artificial Intelligence › Speech Recognition and Synthesis
- Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
- Keywords
- Alzheimer's disease detection, multimodal fusion, speech transcripts, graph neural networks, pre-trained language models, data augmentation, WavLM, contrastive learning
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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