在英国环境中实施人工智能:对人工智能治理的了解,感知到的挑战和机遇,以及放射学家的前进途径
N Stogiannos1, T O'Regan2, E Scurr3
1Division of Midwifery & Radiography, City, University of London, UK; Medical Imaging Department, Corfu General Hospital, Greece.
Radiography (London, England : 1995)
|February 7, 2024
概括
放射科医生需要更好的人工智能 (AI) 培训和更清晰的治理框架,以便在医疗保健中成功实施AI. 解决这些优先事项将有助于利用人工智能的好处,同时最大限度地降低医学成像和放射治疗的风险.
科学领域:
- 医学成像和放射治疗.
- 医疗保健中的人工智能
- 临床实践和技术的采用.
背景情况:
- 人工智能 (AI) 在临床环境中的整合正在迅速扩大,提供了机遇和挑战.
- 关键的实施障碍包括需要明确的治理,有效的AI模型验证和量身定制的放射科医生培训.
研究的目的:
- 探索诊断和治疗放射学家对AI在临床实践中的实施的看法.
- 调查放射学家对人工智能治理,采购,启用器,挑战和未来采用优先事项的知识.
主要方法:
- 一项在线调查分发给英国的放射科医生,他们先前有AI知识.
- 收集了关于人工智能培训,治理意识,实施考虑因素和采用优先事项的数据.
- 描述性统计和千平方测试用于数据分析.
主要成果:
- 大多数被调查的放射科医生 (56.6%) 缺乏针对AI的具体培训.
- 虽然许多人使用了评估框架 (63%),但很大一部分 (36.9%) 仍然对合适的AI模型评估方法不确定.
- 放射学家强调需要明确的人工智能治理,足够的实施时间,资金,领导和支持.
结论:
- 在放射学中成功采用人工智能需要定制培训,强大的治理,利益相关者的参与,以及创造新的专业角色.
- 人工智能实施的优先事项包括开发强大的人工智能治理框架,并为放射科医生提供最佳的人工智能培训.
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