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- Title
Development of a novel scoring system for glaucoma risk based on demographic and laboratory factors using ChatGPT-4.
- Authors
Choi, Joon Yul; Yoo, Tae Keun
- 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.
- Subjects
CHATGPT; MEDICAL sciences; GLAUCOMA; PUBLIC health; ODDS ratio
- Publication
Medical & Biological Engineering & Computing, 2025, Vol 63, Issue 1, p75
- ISSN
0140-0118
- Publication type
Academic Journal
- DOI
10.1007/s11517-024-03182-0