医学医生在COVID-19时代对人工智能的看法:一种混合方法研究
Ashwini S Dongre1, Sandeep D More2, Vidhya Wilson3
1Department of Community Medicine, Government Medical College, Gondia, Maharashtra, India.
Journal of family medicine and primary care
|July 1, 2024
概括
在COVID-19期间,医疗保健中人工智能 (AI) 的采用增加了,在高患者负荷的医生中接受度更高. 然而,人工智能集成面临着挑战,包括教育差距和需要更多的协作开发.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 公共卫生 公共卫生
背景情况:
- 随着COVID-19的流行,大量的人工智能 (AI) 应用得到了推动,但成功程度各不相同.
- 许多人工智能应用程序出现,以应对与流行病相关的挑战,尽管有些人被证明是无效的.
研究的目的:
- 在COVID-19大流行期间评估AI的感知机会和接受.
- 探索医疗数据分析师关于将人工智能整合到医学教育中的观点.
主要方法:
- 采用了混合方法的研究设计.
- 从医生那里收集了定量数据.
- 与医疗数据分析师进行了定性采访.
主要成果:
- 在高COVID-19患者负载设置 (64.8%) 的专业人员对AI工具的接受度显著更高 (P <0.05).
- 医疗数据分析师因学习障碍和层次结构而感到不满,尽管后来得到了认可.
- 医疗数据分析师的工作在流行病后才得到广泛认可.
结论:
- 尽管医生们意识到与流行病相关的压力,但仍然存在大量病例,需要人工智能解决方案.
- 人工智能融入医学落后于技术进步;建议开展意识培训班和合作开发.
- 在正规医学教育中,关于人工智能的机会和应用存在很大的差距.
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