医疗实践中的生成人工智能:对隐私和安全挑战的深入探索
Yan Chen1, Pouyan Esmaeilzadeh1
1Department of Information Systems and Business Analytics, College of Business, Florida International University, Miami, FL, United States.
Journal of medical Internet research
|March 8, 2024
概括
生成型人工智能在医疗保健中提供了变革性的潜力,从诊断到患者护理. 然而,仔细考虑数据隐私和安全风险对于安全实施至关重要.
科学领域:
- 人工智能在医学中的应用
- 医疗保健技术 技术 医疗保健 技术
- 数字健康数字健康
背景情况:
- 人工智能 (AI) 的进步正在彻底改变医疗保健.
- 生成性人工智能模型,包括生成性对抗性网络和大型语言模型,显示出医疗应用的重大前景.
研究的目的:
- 探索医疗保健中的生成性AI应用,例如诊断,药物发现和患者护理.
- 在整个生命周期中识别与生成AI相关的安全和隐私威胁.
- 提出减轻这些风险和确保安全采用战略.
主要方法:
- 对当前在医疗保健中的生成人工智能应用进行文献审查和分析.
- 检查数据收集,模型开发和实施阶段的安全和隐私漏洞.
- 综合发现,为最佳实践和未来发展提供信息.
主要成果:
- 生成型人工智能在医学诊断,药物发现,虚拟助理,研究和临床决策支持方面提供了机会.
- 关键的安全和隐私威胁包括数据泄露,未经授权的访问和道德问题.
- 缓解策略对于负责任地融入医疗保健基础设施至关重要.
结论:
- 解决安全和隐私问题对于在医疗保健中安全有效地使用生成性AI至关重要.
- 了解好处和风险对于医疗保健组织至关重要.
- 这项研究为医疗保健中的AI伦理,安全和数据隐私讨论做出了贡献.
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