Integration of Transformer-Based Architecture and Large Language Models for Optical Coherence Tomography Data Analysis to Improve the Accuracy of Differential Diagnosis of Retinal Diseases.
- DOI
- 10.17691/stm2026.18.3.01
- Published
- 2026
- Container
- Sovremennye tekhnologii v meditsine
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.17691/stm2026.18.3.01,
title = {Integration of Transformer-Based Architecture and Large Language Models for Optical Coherence Tomography Data Analysis to Improve the Accuracy of Differential Diagnosis of Retinal Diseases.},
author = {Konshina OV and Pershin AD and Kulyabin MK and Borisov VI},
year = {2026},
journal = {Sovremennye tekhnologii v meditsine},
doi = {10.17691/stm2026.18.3.01},
url = {https://doi.org/10.17691/stm2026.18.3.01}
}RIS
TY - JOUR TI - Integration of Transformer-Based Architecture and Large Language Models for Optical Coherence Tomography Data Analysis to Improve the Accuracy of Differential Diagnosis of Retinal Diseases. AU - Konshina OV AU - Pershin AD AU - Kulyabin MK AU - Borisov VI PY - 2026 JO - Sovremennye tekhnologii v meditsine DO - 10.17691/stm2026.18.3.01 UR - https://doi.org/10.17691/stm2026.18.3.01 ER -
APA
OV, K., AD, P., MK, K., & VI, B. (2026). Integration of Transformer-Based Architecture and Large Language Models for Optical Coherence Tomography Data Analysis to Improve the Accuracy of Differential Diagnosis of Retinal Diseases.. Sovremennye tekhnologii v meditsine. https://doi.org/10.17691/stm2026.18.3.01
Source records
- pubmed · retrieved 2026-09-25T21:18:40.113Z