论文标题
Chard：文本生成模型跨维度的临床健康感知推理
CHARD: Clinical Health-Aware Reasoning Across Dimensions for Text Generation Models
论文作者
论文摘要
我们激励和介绍了Chard：跨维度的临床健康感知推理，以调查文本生成模型充当隐性临床知识库的能力，并在几个方面生成有关各种与健康相关条件的自由流文字解释。我们收集并介绍了相关的数据集Chardat，其中包括有关三个临床维度的52个健康状况的解释。我们使用BART和T5以及数据增强进行了广泛的实验，并进行自动，人类和定性分析。我们表明，尽管我们的模型可以表现出色，但Chard非常具有挑战性，具有进一步探索的强大潜力。
We motivate and introduce CHARD: Clinical Health-Aware Reasoning across Dimensions, to investigate the capability of text generation models to act as implicit clinical knowledge bases and generate free-flow textual explanations about various health-related conditions across several dimensions. We collect and present an associated dataset, CHARDat, consisting of explanations about 52 health conditions across three clinical dimensions. We conduct extensive experiments using BART and T5 along with data augmentation, and perform automatic, human, and qualitative analyses. We show that while our models can perform decently, CHARD is very challenging with strong potential for further exploration.
