在医疗保健中对ChatGPT和其他对话型大语言模型进行系统审查
Leyao Wang1, Zhiyu Wan2, Congning Ni1
1Department of Computer Science, Vanderbilt University, Nashville, TN, USA, 37212.
概括
大型语言模型 (LLM) 在医疗保健中显示出对总结和医学知识的承诺,但对复杂任务的可靠性问题仍然存在. 未来的研究必须解决LLM偏见和隐私问题,以确保安全的整合.
科学领域:
- 人工智能在医学中的应用
- 在医疗保健中的自然语言处理.
- 数字健康数字健康
背景情况:
- 交谈式大型语言模型 (LLM) 的出现,以ChatGPT为例,激发了对其医疗保健应用的重大兴趣.
- 许多研究探讨了LLM的使用,以帮助患者,临床医生和公共卫生管理人员.
结论:
- 对话式LLM在医疗保健领域有潜力,但对于复杂的应用需要提高可靠性.
- 进一步的研究对于了解和减轻与LLM在医疗保健中的使用相关的偏见和隐私问题至关重要.
- 法律,社会和技术干预是必要的,以确保LLMs的负责任和有效的整合到医疗保健系统.
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