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Diabetes mellitus is a chronic metabolic disorder characterized by high blood glucose levels due to inadequate insulin production, insulin resistance, or both. The condition affects millions worldwide and can significantly impact their health and quality of life.
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在糖尿病管理中安全和安全的AI方法论.

Remco Jan Geukes Foppen1, Vincenzo Gioia2, Shreya Gupta3

  • 1Independent, Anzio, Italy.

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概括

糖尿病管理中的人工智能 (AI) 提供了个性化的护理,但也面临着安全挑战. 可解释的人工智能 (xAI) 对于安全,合规和值得信赖的AI驱动糖尿病解决方案至关重要.

关键词:
在医疗保健中的AI.人工智能的人工智能是人工智能.网络安全 网络安全数据数据的数据数据的数据.可以解释的人工智能AI卫生信息 卫生信息

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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
  • 糖尿病 技术 技术

背景情况:

  • 人工智能 (AI) 有望通过改进的监测和个性化治疗来加强糖尿病管理.
  • 人工智能在糖尿病护理中的临床整合在患者数据安全性,安全性和监管合规性方面存在重大挑战.
  • 对患者健康的潜在直接影响需要仔细考虑人工智能系统的设计和实施.

研究的目的:

  • 为开发人员和研究人员提供指导,以解决糖尿病管理人工智能系统中的安全,保安和合规性挑战.
  • 突出可解释AI (xAI) 在确保AI驱动糖尿病解决方案的安全性,合规性和用户信任方面的关键作用.
  • 检查关键的技术和监管方面,开发可靠和有效的可解释AI应用在糖尿病护理.

主要方法:

  • 分析人工智能系统生命周期,以整合xAI框架,安全措施和风险减轻策略.
  • 在整个AI开发过程中检查构建xAI系统的技术方法.
  • 审查监管框架,包括像FDA这样的机构的治理,风险和合规 (GRC) 标准,用于启用AI的医疗保健应用程序.

主要成果:

  • 了解人工智能系统生命周期是构建强大的xAI框架的关键,这些框架可以解决安全问题并减轻风险.
  • 监管分析确定了GRC必不可少的标准,以确保AI在糖尿病护理中的安全性,有效性和伦理完整性.
  • 整合技术和监管见解为开发可靠的人工智能解决方案提供了一条途径.

结论:

  • 可解释的人工智能 (xAI) 是糖尿病管理中安全,合规和值得信赖的人工智能的基础,增强了临床决策.
  • 解决技术发展和监管要求对于安全有效的AI支持糖尿病护理至关重要.
  • 提供可操作的见解,以促进患者参与,并通过可靠的AI解决方案改善临床结果.