ArticleNPJ digital medicine2024
Prompt engineering in consistency and reliability with the evidence-based guideline for LLMs.
Article in NPJ digital medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 169 papers, 4 of them syntheses that pooled it.
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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.
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Who cites it
169 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Use of large language models for providing automated feedback in medical imaging education: a systematic review.Frontiers in medicine · 2026Pooled it
- Human researchers are superior to large language models in writing a medical systematic review in a comparative multitask assessment.Scientific reports · 2025Pooled it
- AAV Gene Therapy Drug Development and Translation of Engineered Ocular and Neurotropic Capsids: A Systematic Review Using Natural Language Processing.Clinical and translational science · 2025Pooled it
- A comparative study of screening performance between abstrackr and GPT models: Systematic review and contextual analysis.BMC medical informatics and decision making · 2025Pooled it
- Evaluating ChatGPT-4o as an Educational Support Tool for the Emergency Management of Dental Trauma: Randomized Controlled Study Among Students.JMIR medical education · 2025Trial
- Comparing the performance of a large language model and naive human interviewers in interviewing children about a witnessed mock-event.PloS one · 2025Trial
- The Rise of Small Language Models in Healthcare: A Comprehensive Survey.Computer science review · 2026Article
- Performance of large language models in complex coronary artery disease decision-making and potential improvement strategy in a real-world cohort.BMJ health & care informatics · 2026Article
- Prevalent knowledge omissions: An unseen risk of LLMs in patient-friendly adaptation of medical literature.PLOS digital health · 2026Article
- Evaluating Injection Laryngoplasty Skills Using a Foundation Model: A Feasibility Study.The Laryngoscope · 2026Article
- Article
- Multimodal large language models for bladder tumor detection in cystoscopy: a retrospective benchmarking study.World journal of urology · 2026Article
- LungGPT: A unified multimodal system for interpretable diagnosis and clinical decision support of respiratory diseases.Cell reports. Medicine · 2026Article
- Performance of Cloud-Hosted Large Vision-Language Models on the Japanese National Examination for Clinical Laboratory Technicians: Comparative Benchmarking Study.JMIR medical education · 2026Article
- The Impact of Specific Prompt Engineering Techniques on the Readability of LLM-Generated Patient Materials in Gastroenterology and Hepatology.Digestive diseases and sciences · 2026Article
- Generative Large Language Models in Mental Health Care Settings: Systematic Review and Meta-Analysis.JMIR AI · 2026Review
- Ensuring trustworthy AI assisted guideline development for clinical practice.NPJ digital medicine · 2026Article
- Evaluation of Prompt Design and Internal Reasoning in Chatbot-Based Medical History Taking: Simulation Study.JMIR medical informatics · 2026Article
- ChatGPT-4o as a decision-support tool in a urological tumour board: a prospective evaluation.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Article
- OntoCodex: a multi-agent biomedical ontology enrichment framework.npj health systems · 2026Article
109 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The use of large language models (LLMs) in clinical medicine is currently thriving. Effectively transferring LLMs' pertinent theoretical knowledge from computer science to their application in clinical medicine is crucial. Prompt engineering has shown potential as an effective method in this regard. To explore the application of prompt engineering in LLMs and to examine the reliability of LLMs, different styles of prompts were designed and used to ask different LLMs about their agreement with the American Academy of Orthopedic Surgeons (AAOS) osteoarthritis (OA) evidence-based guidelines. Each question was asked 5 times. We compared the consistency of the findings with guidelines across different evidence levels for different prompts and assessed the reliability of different prompts by asking the same question 5 times. gpt-4-Web with ROT prompting had the highest overall consistency (62.9%) and a significant performance for strong recommendations, with a total consistency of 77.5%. The reliability of the different LLMs for different prompts was not stable (Fleiss kappa ranged from -0.002 to 0.984). This study revealed that different prompts had variable effects across various models, and the gpt-4-Web with ROT prompt was the most consistent. An appropriate prompt could improve the accuracy of responses to professional medical questions.
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.