A survey analysis of the adoption of large language models among pathologists

Author:

Laohawetwanit Thiyaphat12ORCID,Pinto Daniel Gomes34ORCID,Bychkov Andrey5ORCID

Affiliation:

1. Division of Pathology, Chulabhorn International College of Medicine, Thammasat University , Pathum Thani , Thailand

2. Division of Pathology, Thammasat University Hospital , Pathum Thani , Thailand

3. Department of Pathology, Hospital Garcia de Orta , Almada , Portugal

4. Nova Medical School , Lisbon , Portugal

5. Department of Pathology, Kameda Medical Center , Kamogawa , Japan

Abstract

Abstract Objectives We sought to investigate the adoption and perception of large language model (LLM) applications among pathologists. Methods A cross-sectional survey was conducted, gathering data from pathologists on their usage and views concerning LLM tools. The survey, distributed globally through various digital platforms, included quantitative and qualitative questions. Patterns in the respondents’ adoption and perspectives on these artificial intelligence tools were analyzed. Results Of 215 respondents, 100 (46.5%) reported using LLMs, particularly ChatGPT (OpenAI), for professional purposes, predominantly for information retrieval, proofreading, academic writing, and drafting pathology reports, highlighting a significant time-saving benefit. Academic pathologists demonstrated a better level of understanding of LLMs than their peers. Although chatbots sometimes provided incorrect general domain information, they were considered moderately proficient concerning pathology-specific knowledge. The technology was mainly used for drafting educational materials and programming tasks. The most sought-after feature in LLMs was their image analysis capabilities. Participants expressed concerns about information accuracy, privacy, and the need for regulatory approval. Conclusions Large language model applications are gaining notable acceptance among pathologists, with nearly half of respondents indicating adoption less than a year after the tools’ introduction to the market. They see the benefits but are also worried about these tools’ reliability, ethical implications, and security.

Publisher

Oxford University Press (OUP)

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. ChatGPT for histopathologic diagnosis;Annals of Diagnostic Pathology;2024-12

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