Evidence map›Paper›PMID 39850627›Full record

ArticleDigital health

Comparing the performance of ChatGPT and ERNIE Bot in answering questions regarding liver cancer interventional radiology in Chinese and English contexts: A comparative study.

Xue-Ting Yuan, Chen-Ye Shao, Zhen-Zhen Zhang, Duo Qian

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Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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5citing papers in PubMed
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1 · What the graph read from 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.

2 · The registry

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Xue-Ting YuanDepartment of Interventional Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China.ORCID https://orcid.org/0009-0004-1073-1541
Chen-Ye ShaoSchool of Nursing, Department of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China.ORCID https://orcid.org/0009-0006-7288-816X
Zhen-Zhen ZhangDepartment of Interventional Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China.ORCID https://orcid.org/0009-0002-6198-9310
Duo QianDepartment of Interventional Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China.ORCID https://orcid.org/0000-0003-2324-7535

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: This study aims to critically assess the appropriateness and limitations of two prominent large language models (LLMs), enhanced representation through knowledge integration (ERNIE Bot) and chat generative pre-trained transformer (ChatGPT), in answering questions about liver cancer interventional radiology. Through a comparative analysis, the performance of these models will be evaluated based on their responses to questions about transarterial chemoembolization and hepatic arterial infusion chemotherapy in both English and Chinese contexts. Methods: A total of 38 questions were developed to cover a range of topics related to transarterial chemoembolization (TACE) and hepatic arterial infusion chemotherapy (HAIC), including foundational knowledge, patient education, and treatment and care. The responses generated by ERNIE Bot and ChatGPT were rigorously evaluated by 10 professionals in liver cancer interventional radiology. The final score was determined by one seasoned clinical expert. Each response was rated on a five-point Likert scale, facilitating a quantitative analysis of the accuracy and comprehensiveness of the information provided by each language model. Results: ERNIE Bot is superior to ChatGPT in the Chinese context (ERNIE Bot: 5, 89.47%; 4, 10.53%; 3, 0%; 2, 0%; 1, 0% vs ChatGPT: 5, 57.89%; 4, 5.27%; 3, 34.21%; 2, 2.63%; 1, 0%; Conclusions: This study preliminarily demonstrated that ERNIE Bot and ChatGPT effectively address questions related to liver cancer interventional radiology. However, their performance varied by language: ChatGPT excelled in English contexts, while ERNIE Bot performed better in Chinese. We found that choosing the appropriate LLMs is beneficial for patients in obtaining more accurate treatment information. Both models require manual review to ensure accuracy and reliability in practical use.

Indexed as

Artificial intelligenceChatGPTERNIE Bothepatic arterial infusion chemo-therapyliver cancertransarterial chemoembolization

Identifiers

PMID39850627
PMCPMC11755525

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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.