论文标题
ITTC @ TREC 2021临床试验轨道
ITTC @ TREC 2021 Clinical Trials Track
论文作者
论文摘要
本文介绍了澳大利亚研究委员会工业转型培训中心（ITTC）的自然语言处理（NLP）团队的意见，用于医疗技术中的认知计算到TREC 2021临床试验轨道。该任务的重点是将合格的临床试验与构成患者入学说明的摘要相匹配的问题。我们探索使用NLP技术来表示试验和主题的不同方法，然后使用常见的检索模型来生成每个主题的相关试验的排名列表。我们所有提交的跑步的结果远高于所有主题的中位数分数，但是仍然有足够的改进范围。
This paper describes the submissions of the Natural Language Processing (NLP) team from the Australian Research Council Industrial Transformation Training Centre (ITTC) for Cognitive Computing in Medical Technologies to the TREC 2021 Clinical Trials Track. The task focuses on the problem of matching eligible clinical trials to topics constituting a summary of a patient's admission notes. We explore different ways of representing trials and topics using NLP techniques, and then use a common retrieval model to generate the ranked list of relevant trials for each topic. The results from all our submitted runs are well above the median scores for all topics, but there is still plenty of scope for improvement.
