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<p>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.</p>

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Application of multimodal large language models for safety indicator calculation and contraindication prediction in laser vision correction

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年2月3日

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  • Joon Yul Choi,
  • Doo Eun Kim,
  • Sung Jin Kim,
  • Hannuy Choi,
  • Tae Keun Yoo

摘要

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.