Comparison of responses from google and large language models to the top frequently asked questions on lumbar spinal stenosis: an evaluation of accuracy and completeness.

Edwin Sun Matthew S Miyasaka Anish Easwaran Samuel Winski Alexander Yu Marlon Murasko Nikhil Adapa M. Murphy Jun-Ho Song Samuel K. Cho

Aug 2026 · European spine journal · 1 citation · 15 references

Medicine

TL;DR

Although newer-generation and search-augmented LLMs demonstrate clear statistical superiority over traditional web results in synthesizing structured spine information, these differences do not yet translate into clinically meaningful quality shifts under concise prompt constraints.

DOI PubMed Semantic Scholar

View source

Similar papers

#small language model Open access Oct 2026

How well do large language models answer postoperative lumbar fusion questions? A blinded comparative analysis of accuracy, quality, readability, and safety-related content

Background Patients recovering from lumbar fusion increasingly seek guidance from large language model (LLM) chatbots when their surgeon is unavailable, but the accuracy, completeness, and safety-related content of such responses have not been compared across models for the postoperative period. Objective To compare th...

Ahmet Kürşat Kara, Ozan Işık · Frontiers in Surgery · 0 citations

Open access Nov 2026

Large Language Models in Shoulder Dislocation: Performance Across Medical and Rehabilitation Domains

Background/Objectives: Large language models (LLMs) are increasingly used to obtain health information about musculoskeletal conditions. However, their performance across different types of clinical questions remains insufficiently understood. This study evaluated the accuracy, quality, information reliability, and rea...

I. Ayas, Ugur Sozlu, B. İnce et al. · Healthcare · 0 citations

Open access Oct 2026

Large language models’ performance in answering common patient questions about colonoscopy: an expert-based evaluation

This study aimed to compare the performance of two large language models (LLMs) the ChatGPT-4 and the Google Bard in delivering medical information about colonoscopy. It also sought to evaluate the models’ responses to common patient and caregiver questions in terms of accuracy, applicability, comprehensiveness, and co...

Neslihan Güneş Aydemi̇r, D. Yapar, Yasemin Demi̇r Avcı et al. · BMC Gastroenterology · 0 citations

Sep 2026

Evaluation of the accuracy and reproducibility of large language models (ChatGPT, DeepSeek, Gemini) in responding to patient-centered lipedema questions.

LLMs can provide generally accurate and consistent responses to patient-centered questions about lipedema, particularly in areas related to general information and diagnosis, however, reduced accuracy and reproducibility in complex clinical domains suggest that expert oversight is essential when using these tools for p...

Rabia Sanır, E. Türkmen, E. Giray et al. · Phlebology · 0 citations

Open access Oct 2026

Quality Assessment of a Large Language Model’s Answers to Frequently Asked Questions About Meniscus Surgery: An Observational Study

To assess the adequacy and the need for adjustment of answers generated by a large language model to common patient questions about meniscus surgery. Ten patient-oriented questions in Portuguese (Brazilian), reflecting frequent pre- and postoperative concerns about meniscus surgery, were submitted to ChatGPT...

R. E. de Paula, R. Reid, P. Maia et al. · Orthopaedic Journal of Sport... · 0 citations

Open access Oct 2026

Comparative evaluation of large language models for esophageal cancer patient education: quality, reliability, readability, understandability, and actionability

Background Large language models (LLMs) are increasingly used as sources of health information. This study evaluated the quality, reliability, readability, understandability, and actionability of responses generated by three mainstream LLMs to esophageal cancer-related questions. Methods Thirty esophageal cancer-relate...

Ying-Ying Hang, Rui-Quan Yuan, Man Lu et al. · Frontiers in Medicine · 0 citations