ArticleCureus2024
Accuracy of ChatGPT in Neurolocalization.
Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Large language models in neurosurgery: a systematic review and meta-analysis.Acta neurochirurgica · 2024Pooled it
- Performance of large language models in interpreting evidence-based clinical guidelines for lumbar disc herniation with radiculopathy.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026Article
- Performance of large language models on neuroanatomy-based medical riddles: a comparative study.Surgical and radiologic anatomy : SRA · 2026Article
- Article
- Referential hallucination and clinical reliability in large language models: a comparative analysis using regenerative medicine guidelines for chronic pain.Rheumatology international · 2025Article
- ReviewGenie: a novel automated system for systematic reviews-an exploratory study in speech and language disorders.Systematic reviews · 2025Article
- The Accuracy of ChatGPT in Answering FAQs, Making Clinical Recommendations, and Categorizing Patient Symptoms: A Literature Review.Advances in health information science and practice · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction ChatGPT (OpenAI Incorporated, Mission District, San Francisco, United States) is an artificial intelligence (AI) chatbot with advanced communication skills and a massive knowledge database. However, its application in medicine, specifically in neurolocalization, necessitates clinical reasoning in addition to deep neuroanatomical knowledge. This article examines ChatGPT's capabilities in neurolocalization. Methods Forty-six text-based neurolocalization case scenarios were presented to ChatGPT-3.5 from November 6th, 2023, to November 16th, 2023. Seven neurosurgeons evaluated ChatGPT's responses to these cases, utilizing a 5-point scoring system recommended by ChatGPT, to score the accuracy of these responses. Results ChatGPT-3.5 achieved an accuracy score of 84.8% in generating "completely correct" and "mostly correct" responses. ANOVA analysis suggested a consistent scoring approach between different evaluators. The mean length of the case text was 69.8 tokens (SD 20.8). Conclusion While this accuracy score is promising, it is not yet reliable for routine patient care. We recommend keeping interactions with ChatGPT concise, precise, and simple to improve response accuracy. As AI continues to evolve, it will hold significant and innovative breakthroughs in medicine.
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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.