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Medical Dialogue Summarization for Automated Reporting in Healthcare

机译:医疗对话中医疗报告的自动汇总

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Healthcare providers generally spend excessive time on administrative tasks at the expense of direct patient care. The emergence of new artificial intelligence and natural language processing technologies gives rise to innovations that could relieve them of this burden. In this paper, we present a pipeline structure for building dialogue summarization systems. Our pipeline summarizes a consultation of a patient with a care provider and automatically generates a report compliant with medical formats. Four pipeline components are used to generate a report based on audio input. The outputs of each component are analyzed to determine the most important challenges and issues. The current proof-of-concept, which was applied to eight doctor-to-patient sessions concerning ear infection, shows that automatic dialogue summarization and reporting is achievable, but requires improvements to increase completeness.
机译:医疗保健提供者通常花费大量时间来执行管理任务,但要以直接患者护理为代价。新的人工智能和自然语言处理技术的出现带来了可以减轻他们负担的创新。在本文中,我们提出了一种用于构建对话摘要系统的管道结构。我们的流程总结了与护理人员的患者咨询情况,并自动生成符合医疗格式的报告。四个管道组件用于基于音频输入生成报告。分析每个组件的输出以确定最重要的挑战和问题。当前的概念验证已应用于涉及耳部感染的八次医生到患者会议中,显示出自动对话摘要和报告是可以实现的,但是需要进行改进以提高完整性。

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