大型语言模型对癌症幸存者和支持性护理的承诺和危险
Danielle S Bitterman1,2, Andrea Downing3, Julia Maués4
1Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA.
概括
利益相关者必须召开会议,制定人工智能在癌症幸存者护理中的未来战略. 这种协作努力对于推进患者支持和长期健康结果至关重要.
科学领域:
- 在瘤学瘤学.
- 医疗信息学 医疗信息学
- 人工智能的人工智能
背景情况:
- 癌症幸存者为患者带来复杂的,长期的挑战.
- 现有的幸存者护理模式需要创新,以满足不断变化的患者需求.
- 大型语言模型 (LLM) 在个性化患者支持方面提供了潜在的进步.
研究的目的:
- 倡导统一的利益相关者在规划LLM增强的癌症幸存者的方法.
- 确定LLM整合在幸存者护理中的关键领域.
- 促进研究人员,临床医生,患者和技术开发人员之间的合作.
主要方法:
- 这是呼吁采取行动,而不是研究.
- 它涉及对LLMs在幸存者的未来应用进行概念化.
- 主要方法是利益相关者参与和战略规划.
主要成果:
- 摘要并没有展示研究结果.
- 它概述了癌症幸存者的未来方向.
- 它强调了需要主动规划和协作.
结论:
- 一个协调的努力是必要的,以利用LLMs在癌症幸存者的潜力.
- 未来的规划应该优先考虑以患者为中心,以技术为导向的支持.
- 让所有利益相关者参与将确保公平有效地实施LLM增强护理.
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