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用人工智能实现黄斑服务的干预设计:一项主要的定性研究.

Henry David Jeffry Hogg1,2,3, Katie Brittain4, James Talks5

  • 1Research, Development and Innovation, University Hospitals Birmingham NHS Foundation Trust, Level 2 ITM, Queen Elizabeth HospitalMindelsohn Way, Birmingham, B15 2GW, UK. J.Hogg.1@bham.ac.uk.

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概括
此摘要是机器生成的。

人工智能 (AI) 可以优化新血管与年龄相关的黄斑变性 (nAMD) 治疗计划. 这项研究指导早期采用者实施人工智能,以改善黄斑服务和患者的治疗结果.

关键词:
人工智能的人工智能是人工智能.临床决策支持 临床决策支持实施 实施 实施机器学习是机器学习.神经血管与年龄相关的黄斑变性.眼科医生 眼科 眼科定性研究是一种定性研究.视网膜 (retina) 是一个视网膜.理论方法理论方法.理论上的理论理论.

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科学领域:

  • 眼科医生 眼科 眼科
  • 医疗信息学 医疗信息学
  • 医疗保健服务研究 医疗服务研究

背景情况:

  • 神经血管与年龄相关的黄斑退化 (nAMD) 显著导致医院门诊预约.
  • 对黄斑服务的临床需求往往超过容量,导致治疗延迟.
  • 人工智能 (AI) 提供了一个潜在的解决方案,以重新平衡黄斑服务的需求和能力.

研究的目的:

  • 为早期采用人工智能的黄斑服务提供指导.
  • 探索影响人工智能支持黄斑服务成功实施的因素.
  • 提供对优化人工智能实施对需求-产能不平衡的见解.

主要方法:

  • 进行了36次半结构面试.
  • 数据使用非采用,放弃,扩大,扩散和可持续性 (NASSS) 框架进行分析.
  • 使用个人,技术和任务之间的适应 (FITT) 框架进行了二次分析,以提出干预措施.

主要成果:

  • 人工智能支持的调度可以保持或增强患者的沟通,同时减少咨询频率.
  • 训练有素的摄影师应该管理AI数据输入和通信,眼科医生提供临床监督.
  • 互操作性需要安全的云图像传输用于AI分析和PACS与EMR集成.

结论:

  • 实现的推动因素众多,与人工智能技术直接相关的障碍很少.
  • 拟议的干预需要当地定制和前性评估.
  • 人工智能实施可以优化,以在黄斑服务中取得成功.