ReviewGlobal spine journal2024
GPT-4 as a Source of Patient Information for Anterior Cervical Discectomy and Fusion: A Comparative Analysis Against Google Web Search.
Review in Global spine journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed.
- Evaluation of Large Language Models in Generating Physical Exercise Rehabilitation Programs for Musculoskeletal Disorders Across Multiple Clinical Scenarios.Healthcare (Basel, Switzerland) · 2026Article
- Can Large Artificial Intelligence-Based Linguistic Models Help to Obtain Information About Burning Mouth Syndrome?Oral diseases · 2026Article
- GPT-4 as a source of patient information for cervical disc arthroplasty: a comparative analysis against Google web search.Journal of spine surgery (Hong Kong) · 2025Article
- Evaluating the Reliability and Quality of Sarcoidosis-Related Information Provided by AI Chatbots.Healthcare (Basel, Switzerland) · 2025Article
- Article
- Is Information About Musculoskeletal Malignancies From Large Language Models or Web Resources at a Suitable Reading Level for Patients?Clinical orthopaedics and related research · 2025Article
- The clinical application potential assessment of the Deepseek-R1 large language model in lung cancer.Frontiers in oncology · 2025Article
- Generative AI/LLMs for Plain Language Medical Information for Patients, Caregivers and General Public: Opportunities, Risks and Ethics.Patient preference and adherence · 2025Review
- The Impact of Google Search versus ChatGPT on Patient Understanding and Potential Adherence in PICC Line Care: A Comparative Analysis.Patient preference and adherence · 2025Article
- ChatGPT-4.0 vs. Google: Which Provides More Academic Answers to Patients' Questions on Arthroscopic Meniscus Repair?Cureus · 2024Article
- Large language models in patient education: a scoping review of applications in medicine.Frontiers in medicine · 2024Article
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
STUDY
designComparative study.
objectivesThis study aims to compare Google and GPT-4 in terms of (1) question types, (2) response readability, (3) source quality, and (4) numerical response accuracy for the top 10 most frequently asked questions (FAQs) about anterior cervical discectomy and fusion (ACDF).
methods"Anterior cervical discectomy and fusion" was searched on Google and GPT-4 on December 18, 2023. Top 10 FAQs were classified according to the Rothwell system. Source quality was evaluated using
resultsFrequently asked questions from Google were varied, while GPT-4 focused on technical details and indications/management. GPT-4 showed a higher Flesch-Kincaid grade level (12.96 vs 9.28,
conclusionsThis study demonstrates GPT-4's ability to elevate patient education by providing high-quality, diverse information tailored to those with advanced literacy levels. As AI technology evolves, refining these tools for accuracy and user-friendliness remains crucial, catering to patients' varying literacy levels and information needs in spine surgery.
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.