| 基于共享编码策略的医学对话阴阳性判别系统 |
| 修订日期：2022-10-22 点此下载全文 |
| 引用本文：姜逸文,伊博乐,陈旭.基于共享编码策略的医学对话阴阳性判别系统[J].医学信息学杂志,2023,44(3):52-58 |
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| 中文摘要:介绍临床发现阴阳性判别任务研究现状,提出一种基于预训练模型的临床发现阴阳性判别系统,详细阐述系统构建方法,分析实验结果,该方法在2021年度中国健康信息处理大会(CHIP 2021)医学对话临床发现阴阳性判别任务的测试集上模型集成Macro-F1值达77.87%。 |
| 中文关键词:在线问诊 阴阳性判别 预训练语言模型 人工智能 自然语言处理 |
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| A Shared Embedding Strategy Based System for Clinical Findings Classification in Medical Dialogues |
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| Abstract:The paper introduces the research status of negative and positive classification tasks in clinical findings, proposes a system for clinical findings classification in medical dialogues based on the pre-trained model, elaborates the construction method of the system and analyzes the experimental results. The proposed method achieves 77.87% of Macro-F1 value in the 7th China health information processing conference (CHIP 2021) classifying positive and negative clinical findings in medical dialogues task. |
| keywords:online consultation positive and negative classification pre-trained language model artificial intelligence(AI) natural language processing (NLP) |
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