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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| Summary: | 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. |
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| ISSN: | 2398-6352 |