核医学技术人员的实践受到了人工智能的影响,拒绝在PET/CT图像中的应用
M Champendal1, R S T Ribeiro2, H Müller3
1School of Health Sciences HESAV, HES-SO, University of Applied Sciences Western Switzerland: Lausanne, CH, Switzerland; Faculty of Biology and Medicine, University of Lausanne, Lausanne, CH, Switzerland.
Radiography (London, England : 1995)
|June 25, 2024
概括
在PET/CT中实施人工智能 (AI) 拒绝需要解决临床实践,工作量和资源. 克服工作流程挑战和缺乏教育等障碍是关键,有明确的解释和支持可以促进采用.
科学领域:
- 医学成像技术 医学成像技术
- 医疗保健中的人工智能
- 辐射科学 辐射科学
背景情况:
- 人工智能 (AI) 具有提高正电子发射断层扫描/计算机断层扫描 (PET/CT) 图像质量的潜力,可以减少注射活动或获取时间.
- 人工智能在临床实践中的成功整合取决于用户的采用,特别是当患者的治疗结果可以得到显著改善时.
- 了解医疗保健专业人员的观点对于有效实施新型人工智能工具至关重要.
研究的目的:
- 确定在临床实践中实施AI拒绝PET/CT算法的关键方面.
- 探索影响核医学技术人员 (NMT) 采用人工智能否定技术的障碍和促进因素.
- 收集来自西瑞士的NMT的见解,以了解人工智能集成的实际考虑.
主要方法:
- 两个焦点小组由来自不同医学成像部门的十名志愿者进行了NMT.
- 基于太华研究使用模式的面试指南指导了讨论.
- 根据万林的三阶段方法,使用内容分析来解释定性数据.
主要成果:
- 四个主要主题出现了:临床实践,工作量,知识和资源,在AI实施之前被确定为关键.
- 关键的障碍包括工作流的挑战,专业的阻力,以及对人工智能的教育不足.
- 收养的促进者包括明确的解释,易于获得的支持和"当地冠军"的存在.
结论:
- 在PET/CT中成功实施AI拒绝算法需要仔细考虑临床程序,工作负载管理和资源配置.
- 通过全面的教育,明确的沟通和强大的支持系统来解决障碍,对于人工智能工具的采用至关重要.
- 该研究强调了以用户为中心的方法的重要性,以有效地将AI整合到诊断成像工作流程中.
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