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Comparative analysis of GPT-4o as a representative multimodal large language model and human fitters in orthokeratology lens fitting: Assessing accuracy, efficiency and cost-effectiveness in initial lens parameter selection
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DOI：10.1111/aos.70185.png)
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Abstract
En 中文
To compare the performance of GPT-4o, used here as a representative multimodal large language model (MLLM), against human fitters in orthokeratology (OK) lens fitting, with a focus on retrospective parameter-matching accuracy, efficiency and cost-effectiveness in initial lens parameter selection.
Keywords:
artificial intelligence
ChatGPT
cost-effectiveness
multimodal large language models
myopia
orthokeratology lenses
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2.8
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1.1W
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1.1W
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