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新冠疫情期间医生对人工智能的认知:一项混合方法研究。

Medical doctor's perception of artificial intelligence during the COVID-19 era: A mixed methods study.

作者信息

Dongre Ashwini S, More Sandeep D, Wilson Vidhya, Singh R Jai

机构信息

Department of Community Medicine, Government Medical College, Gondia, Maharashtra, India.

Department of Neurosurgery, Rajiv Gandhi Institute of Medical Sciences, Adilabad, Telangana State, India.

出版信息

J Family Med Prim Care. 2024 May;13(5):1931-1936. doi: 10.4103/jfmpc.jfmpc_1543_23. Epub 2024 May 24.


DOI:10.4103/jfmpc.jfmpc_1543_23
PMID:38948570
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11213370/
Abstract

BACKGROUND: Artificial intelligence (AI) has led to the development of various opportunities during the COVID-19 pandemic. An abundant number of applications have surfaced responding to the pandemic, while some other applications were futile. OBJECTIVES: The present study aimed to assess the perception and opportunities of AI used during the COVID-19 pandemic and to explore the perception of medical data analysts about the inclusion of AI in medical education. MATERIAL AND METHODS: This study adopted a mixed-method research design conducted among medical doctors for the quantitative part while including medical data analysts for the qualitative interview. RESULTS: The study reveals that nearly 64.8% of professionals were working in high COVID-19 patient-load settings and had significantly more acceptance of AI tools compared to others ( < 0.05). The learning barrier like engaging in new skills and working under a non-medical hierarchy led to dissatisfaction among medical data analysts. There was widespread recognition of their work after the COVID-19 pandemic. CONCLUSION: Notwithstanding that the majority of professionals are aware that public health emergency creates a significant strain on doctors, the majority still have to work in extremely high case load setting to demand solutions. AI applications are still not being integrated into medicine as fast as technology has been advancing. Sensitization workshops can be conducted among specialists to develop interest which will encourage them to identify problem statements in their fields, and along with AI experts, they can create AI-enabled algorithms to address the problems. A lack of educational opportunities about AI in formal medical curriculum was identified.

摘要

背景:在新冠疫情期间,人工智能(AI)带来了各种发展机遇。大量应对疫情的应用出现了,而其他一些应用则毫无成效。 目的:本研究旨在评估新冠疫情期间人工智能应用的认知情况和机遇,并探讨医学数据分析师对在医学教育中纳入人工智能的看法。 材料与方法:本研究采用混合方法研究设计,对医生进行定量研究部分,同时纳入医学数据分析师进行定性访谈。 结果:研究表明,近64.8%的专业人员在新冠患者高负荷环境中工作,与其他人相比,他们对人工智能工具的接受程度明显更高(<0.05)。诸如学习新技能和在非医学层级下工作等学习障碍导致医学数据分析师不满。新冠疫情之后,他们的工作得到了广泛认可。 结论:尽管大多数专业人员意识到公共卫生紧急情况给医生带来了巨大压力,但大多数人仍不得不工作在极高病例负荷的环境中以寻求解决方案。人工智能应用的整合速度仍不及技术进步的速度。可以在专家中举办宣传研讨会以培养兴趣,这将鼓励他们识别所在领域的问题陈述,并与人工智能专家一起创建人工智能算法来解决这些问题。研究发现正规医学课程中缺乏关于人工智能的教育机会。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9ff/11213370/9d28e438e247/JFMPC-13-1931-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9ff/11213370/1dd73bb6837e/JFMPC-13-1931-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9ff/11213370/9d28e438e247/JFMPC-13-1931-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9ff/11213370/1dd73bb6837e/JFMPC-13-1931-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9ff/11213370/9d28e438e247/JFMPC-13-1931-g002.jpg

相似文献

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Medical doctor's perception of artificial intelligence during the COVID-19 era: A mixed methods study.

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[9]
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引用本文的文献

[1]
Physicians' attitudes and acceptance towards artificial intelligence in medical care: a qualitative study in Germany.

Front Digit Health. 2025-7-14

[2]
Exploring the role of moxibustion robots in teaching: a cross-sectional study.

BMC Med Educ. 2025-1-13

本文引用的文献

[1]
Acceptance of clinical artificial intelligence among physicians and medical students: A systematic review with cross-sectional survey.

Front Med (Lausanne). 2022-8-31

[2]
Attitudes and Acceptance Towards Artificial Intelligence in Medical Care.

Stud Health Technol Inform. 2022-5-25

[3]
Covid-19 Infection in India: A Comparative Analysis of the Second Wave with the First Wave.

Pathogens. 2021-9-21

[4]
Artificial intelligence: opportunities and risks for public health.

Lancet Digit Health. 2019-5

[5]
Artificial Intelligence (AI) applications for COVID-19 pandemic.

Diabetes Metab Syndr. 2020

[6]
Correlation of Chest CT and RT-PCR Testing for Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases.

Radiology. 2020-2-26

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