ArticleJournal of personalized medicine2023
Navigating the Landscape of Personalized Medicine: The Relevance of ChatGPT, BingChat, and Bard AI in Nephrology Literature Searches.
Article in Journal of personalized medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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
20 citing papers in PubMed, 1 synthesis or guideline pooled it, 39 citations in OpenAlex.
- The emergence of large language models as tools in literature reviews: a large language model-assisted systematic review.Journal of the American Medical Informatics Association : JAMIA · 2025Pooled it
- Utilization and prospects of artificial intelligence in the diagnosis, prediction, and treatment of erectile dysfunction.Sexual medicine · 2026Review
- Quality assessment of large language model-generated prior authorization letters in nephrology.Frontiers in digital health · 2026Article
- Evaluating the Accuracy of Responses by Large Language Models for Information on Disease Epidemiology.Pharmacoepidemiology and drug safety · 2025Article
- PICOT questions and search strategies formulation: A novel approach using artificial intelligence automation.Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing · 2025Article
- Performance of o1 pro and GPT-4 in Self-Assessment Questions for Nephrology Board Renewal.Frontiers in medicine · 2025Article
- How to incorporate generative artificial intelligence in nephrology fellowship education.Journal of nephrology · 2024Article
- RefAI: a GPT-powered retrieval-augmented generative tool for biomedical literature recommendation and summarization.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- The transformative impact of large language models on medical writing and publishing: current applications, challenges and future directions.The Korean journal of physiology & pharmacology : official journal of the Korean Physiological Society and the Korean Society of Pharmacology · 2024Review
- Joint Expedition: Exploring the Intersection of Digital Health and AI in Precision Medicine with Team Integration.Journal of personalized medicine · 2024Article
- Integrating Retrieval-Augmented Generation with Large Language Models in Nephrology: Advancing Practical Applications.Medicina (Kaunas, Lithuania) · 2024Review
- A Preliminary Checklist (METRICS) to Standardize the Design and Reporting of Studies on Generative Artificial Intelligence-Based Models in Health Care Education and Practice: Development Study Involving a Literature Review.Interactive journal of medical research · 2024Article
- Artificial Intelligence in Kidney Disease: A Comprehensive Study and Directions for Future Research.Diagnostics (Basel, Switzerland) · 2024Review
- Article
- Personalized Medicine in Urolithiasis: AI Chatbot-Assisted Dietary Management of Oxalate for Kidney Stone Prevention.Journal of personalized medicine · 2024Article
- Chain of Thought Utilization in Large Language Models and Application in Nephrology.Medicina (Kaunas, Lithuania) · 2024Review
- Innovating Personalized Nephrology Care: Exploring the Potential Utilization of ChatGPT.Journal of personalized medicine · 2023Review
- Personalized Care in Eye Health: Exploring Opportunities, Challenges, and the Road Ahead for Chatbots.Journal of personalized medicine · 2023Review
- The Utility of ChatGPT for Assisting Patients with Study Preparation and Report Interpretation of Myocardial Viability Scintigraphy: Exploring the Future of AI-driven Patient Comprehension in Nuclear Medicine.Indian journal of nuclear medicine : IJNM : the official journal of the Society of Nuclear Medicine, IndiaArticle
- 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
7 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectivesLiterature reviews are foundational to understanding medical evidence. With AI tools like ChatGPT, Bing Chat and Bard AI emerging as potential aids in this domain, this study aimed to individually assess their citation accuracy within Nephrology, comparing their performance in providing precise. MATERIALS AND
methodsWe generated the prompt to solicit 20 references in Vancouver style in each 12 Nephrology topics, using ChatGPT, Bing Chat and Bard. We verified the existence and accuracy of the provided references using PubMed, Google Scholar, and Web of Science. We categorized the validity of the references from the AI chatbot into (1) incomplete, (2) fabricated, (3) inaccurate, and (4) accurate.
resultsA total of 199 (83%), 158 (66%) and 112 (47%) unique references were provided from ChatGPT, Bing Chat and Bard, respectively. ChatGPT provided 76 (38%) accurate, 82 (41%) inaccurate, 32 (16%) fabricated and 9 (5%) incomplete references. Bing Chat provided 47 (30%) accurate, 77 (49%) inaccurate, 21 (13%) fabricated and 13 (8%) incomplete references. In contrast, Bard provided 3 (3%) accurate, 26 (23%) inaccurate, 71 (63%) fabricated and 12 (11%) incomplete references. The most common error type across platforms was incorrect DOIs.
conclusionsIn the field of medicine, the necessity for faultless adherence to research integrity is highlighted, asserting that even small errors cannot be tolerated. The outcomes of this investigation draw attention to inconsistent citation accuracy across the different AI tools evaluated. Despite some promising results, the discrepancies identified call for a cautious and rigorous vetting of AI-sourced references in medicine. Such chatbots, before becoming standard tools, need substantial refinements to assure unwavering precision in their outputs.
Indexed as
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.