Suppr超能文献

放射科医生和实习生对采用类似GPT技术的态度:一项中国的全国性调查研究。

Attitudes of radiologists and interns toward the adoption of GPT-like technologies: a National Survey Study in China.

作者信息

Xia Tianyi, Zhang Shijun, Zhao Ben, Lei Ying, Xiao Zebin, Chen Bingwei, Zha Junhao, Yu Yaoyao, Wu Zhijun, Lu Chunqiang, Tang Tianyu, Song Yang, Wang Yuancheng, Ju Shenghong

机构信息

Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology (Southeast University), Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China.

Department of Biomedical Sciences, University of Pennsylvania, Philadelphia, PA, USA.

出版信息

Insights Imaging. 2025 Jan 31;16(1):30. doi: 10.1186/s13244-025-01908-8.

Abstract

OBJECTIVES

To investigate the attitudes of Chinese radiologists or interns towards generative pre-trained (GPT)-like technologies.

METHODS

A prospective survey was distributed to 1339 Chinese radiologists or interns via an online platform from October 2023 to May 2024. The questionnaire covered respondent characteristics, opinions on using GPT-like technologies (in clinical practice, training and education, environment and regulation, and development trends), and their attitudes toward these technologies. Logistic regression was conducted to identify underlying factors associated with the attitude.

RESULTS

After quality control, 1289 respondents (median age, 37.0 years [IQR, 31.0-44.0 years]; 813 males) were surveyed. Most of the respondents (n = 1223, 94.9%) supported adoption of GPT-like technologies. Based on the acceptance level of GPT-like technologies, the respondents were 3 (0.2%), 29 (2.2%), 352 (27.3%), 677 (52.5%), and 228 (17.7%) from low to high acceptance degrees. Multivariable analysis revealed significant associations between positive attitudes towards GPT-like technologies and their acceptance: writing papers and language polishing (odds ratio [OR] = 1.99; p < 0.001), influence of colleagues using such technologies (OR = 1.77; p = 0.007), government regulation introduction (OR = 2.25; p < 0.001), and enhancement of decision support capabilities (OR = 2.67; p < 0.001). Sensitivity analyses confirmed these results for different acceptance thresholds (all p < 0.001).

CONCLUSIONS

Chinese radiologists or interns generally support GPT-like technologies due to their potential capabilities in clinical practice, medical education, and scientific research. They also emphasize the need for regulatory oversight and remain optimistic about their future medical applications.

CRITICAL RELEVANCE STATEMENT

This study highlights the broad support among Chinese radiologists for GPT-like technologies, emphasizing their potential to enhance clinical decision-making, streamline medical education, and improve research efficiency, while underscoring the need for regulatory oversight.

KEY POINTS

The impact of GPT-like technologies on the radiology field is unclear. Most Chinese radiologists express the supportive adoption of GPT-like technologies. GPT-like technologies' capabilities at research and clinic prompt the attitude.

摘要

目的

调查中国放射科医生或实习生对类似生成式预训练(GPT)技术的态度。

方法

2023年10月至2024年5月,通过在线平台向1339名中国放射科医生或实习生进行了一项前瞻性调查。问卷涵盖受访者特征、对使用类似GPT技术的看法(在临床实践、培训与教育、环境与监管以及发展趋势方面),以及他们对这些技术的态度。进行逻辑回归以确定与态度相关的潜在因素。

结果

经过质量控制,共调查了1289名受访者(年龄中位数为37.0岁[四分位间距,31.0 - 44.0岁];男性813名)。大多数受访者(n = 1223,94.9%)支持采用类似GPT的技术。根据对类似GPT技术的接受程度,受访者从低到高接受程度的人数分别为3名(0.2%)、29名(2.2%)、352名(27.3%)、677名(52.5%)和228名(17.7%)。多变量分析显示,对类似GPT技术的积极态度与其接受程度之间存在显著关联:撰写论文和语言润色(比值比[OR] = 1.99;p < 0.001)、同事使用此类技术的影响(OR = 1.77;p = 0.007)、政府出台监管措施(OR = 2.25;p < 0.001)以及决策支持能力的提升(OR = 2.67;p < 0.001)。敏感性分析针对不同接受阈值证实了这些结果(所有p < 0.001)。

结论

中国放射科医生或实习生普遍支持类似GPT的技术,因为其在临床实践、医学教育和科研方面具有潜在能力。他们还强调需要监管监督,并对其未来的医学应用持乐观态度。

关键相关性声明

本研究突出了中国放射科医生对类似GPT技术的广泛支持,强调了它们在增强临床决策、简化医学教育和提高研究效率方面的潜力,同时强调了监管监督的必要性。

要点

类似GPT的技术对放射学领域的影响尚不清楚。大多数中国放射科医生表示支持采用类似GPT的技术。类似GPT的技术在研究和临床方面的能力促使了这种态度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4b31/11785863/d461d8624995/13244_2025_1908_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验