HealthFC：基于证据的医学事实核查验证健康声明
HealthFC: Verifying Health Claims with Evidence-Based Medical Fact-Checking
AI总结：
本文提出健康事实核查数据集HealthFC，包含750条带专家标注和证据支持的健康声明，用于推进自动化事实核查NLP任务，并提供基线系统验证其挑战性与潜力。
摘要：
在数字时代，在互联网上寻求健康建议已成为一种常见做法。同时，判断在线医疗内容的可信度也变得越来越具有挑战性。事实核查已成为一种利用来自可靠知识源的证据来评估事实声明真实性的方法。为了帮助推进针对该任务的自动化自然语言处理（NLP）解决方案，本文引入了一个新颖的数据集HealthFC。它包含750条德语和英语的健康相关声明，由医学专家进行真实性标注，并有来自系统评价和临床试验的证据支持。我们对数据集进行了分析，突出了其特征与挑战。该数据集可用于与自动化事实核查相关的NLP任务，例如证据检索、声明验证或解释生成。出于测试目的，我们提供了基于不同方法的基线系统，检查了它们的性能并讨论了研究结果。我们表明，该数据集是一个具有挑战性的测试平台，在未来具有很高的使用潜力。
英文摘要：
In the digital age, seeking health advice on the Internet has become a common practice. At the same time, determining the trustworthiness of online medical content is increasingly challenging. Fact-checking has emerged as an approach to assess the veracity of factual claims using evidence from credible knowledge sources. To help advance automated Natural Language Processing (NLP) solutions for this task, in this paper we introduce a novel dataset HealthFC. It consists of 750 health-related claims in German and English, labeled for veracity by medical experts and backed with evidence from systematic reviews and clinical trials. We provide an analysis of the dataset, highlighting its characteristics and challenges. The dataset can be used for NLP tasks related to automated fact-checking, such as evidence retrieval, claim verification, or explanation generation. For testing purposes, we provide baseline systems based on different approaches, examine their performance, and discuss the findings. We show that the dataset is a challenging test bed with a high potential for future use.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
