图 书 馆
使用端到端多任务学习模型的Naranjo问答Naranjo Question Answering using End-to-End Multi-task Learning Model |
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| 课程网址: | http://videolectures.net/kdd2019_rawat_yu_naranjo/ |
| 主讲教师: | Bhanu Pratap Singh Rawat |
| 开课单位: | 马萨诸塞大学阿默斯特分校 |
| 开课时间: | 2020-03-02 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | In the clinical domain, it is important to understand whether an adverse drug reaction (ADR) is caused by a particular medication. Clinical judgement studies help judge the causal relation between a medication and its ADRs. In this study, we present the first attempt to automatically infer the causality between a drug and an ADR from electronic health records (EHRs) by answering the Naranjo questionnaire, the validated clinical question answering set used by domain experts for ADR causality assessment. Using physicians’ annotation as the gold standard, our proposed joint model, which uses multi-task learning to predict the answers of a subset of the Naranjo questionnaire, significantly outperforms the baseline pipeline model with a good margin, achieving a macro-weighted f-score between 0.3652-0.5271 and micro-weighted f-score between 0.9523-0.9918. |
| 关 键 词: | 使用端到端多任务学习; 多任务学习模型; Naranjo问答 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2022-09-19：cyh |
| 最后编审: | 2022-09-19：cyh |
| 阅读次数: | 34 |