确保一个生成性AI驱动的医疗保健聊天机器人
Georgios Feretzakis1, Athanasios Anastasiou2, Stavros Pitoglou3
1School of Science and Technology, Hellenic Open University, Patras, Greece.
Studies in health technology and informatics
|November 22, 2024
概括
生成型人工智能 (AI) 和大型语言模型 (LLM) 增强了医疗保健,但需要安全,道德的部署. 本文提出了一条管道,以确保数据隐私,弹性和用户对人工智能医疗聊天机器人的信任.
科学领域:
- 医疗保健技术 医疗保健技术 医疗保健技术
- 人工智能在医学中的应用
- 数字健康数字健康
背景情况:
- 像GPT-4,Gemini,Claude和Llama这样的大型语言模型 (LLM) 正在改变医疗保健服务.
- 医疗保健中的AI应用包括患者护理,医学研究和行政效率.
- 目前的人工智能采用面临着重大的安全和道德障碍,包括数据隐私问题.
研究的目的:
- 为部署人工智能驱动的医疗保健聊天机器人提出安全和道德框架.
- 解决数据隐私,安全和用户对人工智能医疗保健应用程序的信任方面的挑战.
- 提高人工智能系统在敏感医疗环境中的弹性和可靠性.
主要方法:
- 将先进的隐私保护技术集成到AI聊天机器人管道中.
- 实施人工智能医疗保健系统的持续安全评估.
- 为医疗环境中的生成人工智能量身定制的伦理准则的制定.
主要成果:
- 拟议的管道增强了人工智能医疗聊天机器人的数据隐私和安全性.
- 持续的安全评估提高了人工智能系统对潜在威胁的弹性.
- 该框架旨在促进用户对人工智能驱动的医疗保健解决方案更大的信任.
结论:
- 安全和道德的管道对于在医疗保健中负责任地部署人工智能至关重要.
- 解决安全和道德方面的考虑对于实现人工智能聊天机器人的全部潜力至关重要.
- 拟议的方法提供了一个可靠的模型,用于在患者护理和医学研究中可靠的AI集成.
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