Benchmarking Zero-Shot Generative Pre-Trained Transformer-Based Multimodal Large Language Models for Pressure Injury Staging
- DOI
- 10.1177/21621918261465916
- Published
- 2026-07-03
- Container
- Advances in Wound Care
- Publisher
- SAGE Publications
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1177/21621918261465916,
title = {Benchmarking Zero-Shot Generative Pre-Trained Transformer-Based Multimodal Large Language Models for Pressure Injury Staging},
author = {Toshiaki Takahashi and Kengo Miyo and Nao Tamai},
year = {2026},
journal = {Advances in Wound Care},
doi = {10.1177/21621918261465916},
url = {https://doi.org/10.1177/21621918261465916}
}RIS
TY - JOUR TI - Benchmarking Zero-Shot Generative Pre-Trained Transformer-Based Multimodal Large Language Models for Pressure Injury Staging AU - Toshiaki Takahashi AU - Kengo Miyo AU - Nao Tamai PY - 2026 JO - Advances in Wound Care DO - 10.1177/21621918261465916 UR - https://doi.org/10.1177/21621918261465916 ER -
APA
Takahashi, T., Miyo, K., & Tamai, N. (2026). Benchmarking Zero-Shot Generative Pre-Trained Transformer-Based Multimodal Large Language Models for Pressure Injury Staging. Advances in Wound Care. https://doi.org/10.1177/21621918261465916
Source records
- crossref · retrieved 2026-09-26T12:33:19.875Z