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医学中的生成人工智能

Divya Shanmugam1, Monica Agrawal2,3, Rajiv Movva1

  • 11Department of Computer Science, Cornell Tech, New York, NY, USA.

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概括
此摘要是机器生成的。

生成型人工智能 (AI) 为各种医疗保健专业人员和患者提供了新的医疗应用. 实现人工智能的潜力需要解决隐私,透明度,公平性和模型评估方面的关键挑战.

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科学领域:

  • 医疗信息学 医疗信息学
  • 人工智能的人工智能
  • 医疗保健技术 技术 医疗保健 技术

背景情况:

  • 生成型人工智能 (AI) 能力正在迅速发展.
  • 这些进步在医学领域具有众多的潜在应用.

研究的目的:

  • 为医学中生成性AI使用案例提供全面的概述.
  • 识别和讨论阻碍在医疗保健中采用生成AI的挑战.
  • 突出医学中生成性AI的开放研究方向.

主要方法:

  • 文献综述和综合医学当前的生成AI应用.
  • 分析与隐私,安全,透明度,可解释性,公平性和模型评估相关的挑战.
  • 确定未来的研究途径.

主要成果:

  • 生成型人工智能对临床医生,患者,试验组织者,研究人员和实习生有多种应用.
  • 存在重大挑战,包括数据隐私,模型透明度,公平访问和严格验证.
  • 有许多研究机会来克服这些障碍.

结论:

  • 生成性人工智能在医疗保健和医学研究方面具有变革性的潜力.
  • 解决伦理,技术和实际挑战对于成功实施至关重要.
  • 持续的研究对于释放医学中生成性AI的全部好处至关重要.