ArticleCureus2025
Evaluation of Artificial Intelligence for Patient Self-Triage: Comparison of General-Purpose AI Platforms With the NHS 111 Online Symptom Checker in the United Kingdom.
Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
2 citing papers in PubMed.
- Increasing Large Language Model Accuracy for Care-Seeking Advice Using Prompts Reflecting Human Reasoning Strategies in the Real World: Validation Study.JMIR biomedical engineering · 2026Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Emergency departments (EDs) in the UK face substantial pressure due to non-urgent attendances. This technical report evaluates the performance of two general-purpose artificial intelligence (AI) platforms (ChatGPT GPT-5 (OpenAI, San Francisco, California, USA) and Gemini AI v2.5 Flash (Google, Mountain View, California, USA)) for patient self-triage, compared with the NHS 111 online symptom checker. Ten simulated patient scenarios, including five emergency and five non-emergency cases, were assessed against National Institute for Health and Care Excellence (NICE) guideline-based gold standards. Both AI platforms correctly identified all emergency cases; NHS 111 under-triaged one acute emergency. For non-emergency scenarios, AI occasionally over-triaged, recommending emergency assessment for pyelonephritis, whereas NHS 111 correctly classified all non-emergencies. AI triage responses were faster and required fewer follow-up questions than NHS 111, although sometimes producing unclear recommendations. The findings suggest that general-purpose AI may serve as an adjunct to NHS 111, supporting patient self-triage and potentially reducing ED burden. Future work should include larger-scale testing, real patient data, and prospective safety evaluation to assess clinical feasibility.
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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.