CanerClarity App:通过人工智能生成的叙述来增强癌症数据可视化
Edgar Munoz1, Alexander D VanHelene2, Nuen Tsang Yang3
1The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
概括
癌症明确应用程序使用人工智能 (AI) 和大型语言模型 (LLM) 来将复杂的癌症统计数据转化为易于理解的叙述. 该工具增强了癌症中心的沟通,改善了公共卫生决策.
科学领域:
- 公共卫生信息学 公共卫生信息学
- 卫生传播健康传播
- 数据科学数据科学数据科学
背景情况:
- 由于资源有限,社区癌症中心难以获取和传达重要的癌症数据.
- 对患者和社区成员来说,有效的健康信息沟通至关重要.
研究的目的:
- 推出CancerClarity应用程序,这是一个创新的工具,旨在弥合癌症数据可访问性和沟通方面的差距.
- 利用人工智能 (AI) 和大型语言模型 (LLM) 来生成可访问的癌症数据叙述.
主要方法:
- 癌症Clarity应用程序在R Shiny框架内使用LLM提示,整合了来自癌症InFocus的数据.
- 它提供了美国各县癌症发病率,死亡率和健康决定因素的交互式数据可视化.
主要成果:
- 该应用程序通过API集成LLMs实时,定制叙述,使复杂的癌症数据可访问.
- 它为癌症中心提供了一种具有成本效益的解决方案,以确定流域并评估人口癌症负担.
结论:
- 人工智能驱动的叙述通过改善癌症数据的沟通来增强公共卫生决策.
- 未来的发展包括用于增强人工智能响应和基于证据的指导的提取增强生成 (RAG).
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