ArticleNPJ digital medicine2025
Application of multimodal large language models for safety indicator calculation and contraindication prediction in laser vision correction.
Article in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- Report Generation System for Slit-Lamp Image Interpretation Using Vision-Language Models.Ophthalmology and therapy · 2026Article
- Article
- Prediction of refractive error in adolescents using a multimodal large language model.Frontiers in medicine · 2026Article
- Large language models for ophthalmic examination understanding: from information extraction to clinical decision support.Frontiers in medicine · 2026Review
- Accuracy of ChatGPT, Gemini, Copilot, and Claude to Blepharoplasty-Related Questions.Aesthetic plastic surgery · 2025Article
- Codeless Development of a Customized SMILE Nomogram Using a Large Language Model: A Practical Framework for Clinicians.Journal of ophthalmology · 2025Article
- Application prospect of large language model represented by ChatGPT in ophthalmology.International journal of ophthalmology · 2025Review
- Multimodal LLMs for retinal disease diagnosis via OCT: few-shot versus single-shot learning.Therapeutic advances in ophthalmologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.