Application of multimodal large language models for safety indicator calculation and contraindication prediction in laser vision correction
Abstract This study demonstrates the potential of multimodal large language models in calculating safety indicators and predicting contraindications for laser vision correction. ChatGPT-4 effectively analyzed ocular data, calculated key indicators, generated calculator codes, and outperformed tradit...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-02-01
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| Series: | npj Digital Medicine |
| Online Access: | https://doi.org/10.1038/s41746-025-01487-4 |
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| _version_ | 1823861587113410560 |
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| author | Joon Yul Choi Doo Eun Kim Sung Jin Kim Hannuy Choi Tae Keun Yoo |
| author_facet | Joon Yul Choi Doo Eun Kim Sung Jin Kim Hannuy Choi Tae Keun Yoo |
| author_sort | Joon Yul Choi |
| collection | DOAJ |
| description | Abstract This study demonstrates the potential of multimodal large language models in calculating safety indicators and predicting contraindications for laser vision correction. ChatGPT-4 effectively analyzed ocular data, calculated key indicators, generated calculator codes, and outperformed traditional machine learning models and indicators in handling unstructured data and corneal topography. Its modality-independent system enabled efficient and accurate data analysis. Despite longer processing times, ChatGPT-4’s performance highlights its potential as a decision-support tool, offering advancements in improving safety. |
| format | Article |
| id | doaj-art-b83946345caf49baaa977df8e1e6890f |
| institution | Kabale University |
| issn | 2398-6352 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Digital Medicine |
| spelling | doaj-art-b83946345caf49baaa977df8e1e6890f2025-02-09T12:55:43ZengNature Portfolionpj Digital Medicine2398-63522025-02-01811910.1038/s41746-025-01487-4Application of multimodal large language models for safety indicator calculation and contraindication prediction in laser vision correctionJoon Yul Choi0Doo Eun Kim1Sung Jin Kim2Hannuy Choi3Tae Keun Yoo4Department of Biomedical Engineering, Yonsei UniversityKim Eye ClinicKim Eye ClinicDepartment of Refractive Surgery, B&VIIT Eye CenterDepartment of Ophthalmology, Hangil Eye HospitalAbstract This study demonstrates the potential of multimodal large language models in calculating safety indicators and predicting contraindications for laser vision correction. ChatGPT-4 effectively analyzed ocular data, calculated key indicators, generated calculator codes, and outperformed traditional machine learning models and indicators in handling unstructured data and corneal topography. Its modality-independent system enabled efficient and accurate data analysis. Despite longer processing times, ChatGPT-4’s performance highlights its potential as a decision-support tool, offering advancements in improving safety.https://doi.org/10.1038/s41746-025-01487-4 |
| spellingShingle | Joon Yul Choi Doo Eun Kim Sung Jin Kim Hannuy Choi Tae Keun Yoo Application of multimodal large language models for safety indicator calculation and contraindication prediction in laser vision correction npj Digital Medicine |
| title | Application of multimodal large language models for safety indicator calculation and contraindication prediction in laser vision correction |
| title_full | Application of multimodal large language models for safety indicator calculation and contraindication prediction in laser vision correction |
| title_fullStr | Application of multimodal large language models for safety indicator calculation and contraindication prediction in laser vision correction |
| title_full_unstemmed | Application of multimodal large language models for safety indicator calculation and contraindication prediction in laser vision correction |
| title_short | Application of multimodal large language models for safety indicator calculation and contraindication prediction in laser vision correction |
| title_sort | application of multimodal large language models for safety indicator calculation and contraindication prediction in laser vision correction |
| url | https://doi.org/10.1038/s41746-025-01487-4 |
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