The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Self-supervised Predictive Coding with Multimodal Fusion for Patient Deterioration Prediction in Fine-Grained Time Resolution
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Attention mechanisms such as gated attention, cross-attention, or transformer encoders are increasingly adopted in multimodal AI.
“attention mechanisms such as gated attention [40,41], cross-attention [42–45], or transformer encoders [20,36,46–49] are increasingly adopted.”
From Multimodal Artificial Intelligence for Precision Critical Care: A Scoping Review (2026) · cites this paper as [36]
Only a small number of studies connected multimodal predictions to clinical interventions.
“Only a small number of studies connected multimodal predictions to clinical interventions [36–39]”
From Multimodal Artificial Intelligence for Precision Critical Care: A Scoping Review (2026) · cites this paper as [36]
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Multimodal Transformer for Unaligned Multimodal Language Sequences
Tsai, Y.-H. H., Bai, S., Liang, P. P., Kolter, J. Z., Morency, L.-P., & Salakhutdinov, R. (2019) · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics · doi:10.18653/v1/p19-1656 · Cited by 2,259
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Multimodal Artificial Intelligence for Precision Critical Care: A Scoping Review
Yang, M., Shi, N., Chen, H., Po, E. Y. P., Ng, P. Y., Lai, P. C. K., Wu, Y.-C., & Fong, D. Y. T. (2026) · Health Data Science · doi:10.34133/hds.0356 · Cited by 3
“While simple concatenation of deeply extracted features remains the most straightforward approach, attention mechanisms such as gated attention [ 40 , 41 ], cross-attention [ 42 – 45 ], or trans-former encoders [ 20 , 36 , 46 – 49 ] are increasingly adopted.”
Metadata
- Authors
- Lee, K., Won, J., Hyun, H., Hahn, S., Choi, E., & Lee, J.
- Affiliations
- Pohang University of Science and Technology (KR)
- Korea Advanced Institute of Science and Technology (KR)
- Corresponding author
- Lee, Joohyung
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Nature Switzerland
- Published
- 2023
- Pages
- 41-50
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W4385377104
- Cited by
- 5
- References
- 1
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 3
- FWCI
- 0.89
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Licence
- Locations
- Lecture notes in computer science (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University) (cc-by)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning in Healthcare
- Health Sciences › Medicine › Critical Care and Intensive Care Medicine › Sepsis Diagnosis and Treatment
- Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
- Keywords
- clinical deterioration prediction, multimodal fusion, mortality prediction, electronic health records, intensive care unit, emergency department, critical care decision-making
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