ArticleMedical & biological engineering & computing2025
Development of a novel scoring system for glaucoma risk based on demographic and laboratory factors using ChatGPT-4.
Article in Medical & biological engineering & computing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Applications of Large Language Models in Glaucoma: A Scoping Review.Vision (Basel, Switzerland) · 2026Review
- Automated detection of retinal artery occlusion in fundus photography via self-supervised deep learning and multimodal interpretability using a multimodal AI chatbot.Medical & biological engineering & computing · 2025Article
- Retinal vein occlusion risk prediction without fundus examination using a no-code machine learning tool for tabular data: a nationwide cross-sectional study from South Korea.BMC medical informatics and decision making · 2025Article
- Large language models in the management of chronic ocular diseases: a scoping review.Frontiers in cell and developmental biology · 2025Review
- Assessment of Large Language Models in Cataract Care Information Provision: A Quantitative Comparison.Ophthalmology and therapy · 2025Article
- Application prospect of large language model represented by ChatGPT in ophthalmology.International journal of ophthalmology · 2025Review
- Application of ChatGPT-4 to oculomics: a cost-effective osteoporosis risk assessment to enhance management as a proof-of-principles model in 3PM.The EPMA journal · 2024Article
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Authors and funding
2 authors.
Funding
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Abstract
We developed a scoring system for assessing glaucoma risk using demographic and laboratory factors by employing a no-code approach (automated coding) using ChatGPT-4. Comprehensive health checkup data were collected from the Korea National Health and Nutrition Examination Survey. Using ChatGPT-4, logistic regression was conducted to predict glaucoma without coding or manual numerical processes, and the scoring system was developed based on the odds ratios (ORs). ChatGPT-4 also facilitated the no-code creation of an easy-to-use risk calculator for glaucoma. The ORs for the high-risk groups were calculated to measure performance. ChatGPT-4 automatically developed a scoring system based on demographic and laboratory factors, and successfully implemented a risk calculator tool. The predictive ability of the scoring system was comparable to that of traditional machine learning approaches. For high-risk groups with 1-2, 3-4, and 5 + points, the calculated ORs for glaucoma were 1.87, 2.72, and 15.36 in the validation set, respectively, compared with the group with 0 or fewer points. This study presented a novel no-code approach for developing a glaucoma risk assessment tool using ChatGPT-4, highlighting its potential for democratizing advanced predictive analytics, making them readily available for clinical use in glaucoma detection.
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Registered trials
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