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GRACE: Generating Summary Reports Automatically for Cognitive Assistance in Emergency Response

机译:Grace:在紧急响应中自动生成摘要报告,以便在紧急响应中进行认知援助

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EMS (emergency medical service) plays an important role in saving lives in emergency and accident situations. When first responders, including EMS providers and firefighters, arrive at an incident, they communicate with the patients (if conscious), family members and other witnesses, other first responders, and the command center. The first responders utilize a microphone and headset to support these communications. After the incident, the first responders are required to document the incident by filling out a form. Today, this is performed manually. Manual documentation of patient summary report is time-consuming, tedious, and error-prone. We have addressed these form filling problems by transcribing the audio from the scene, identifying the relevant information from all the conversations, and automatically filling out the form. Informal survey of first responders indicate that this application would be exceedingly helpful to them. Results show that we can fill out a model summary report form with an F1 score as high as 94%, 78%, 96%, and 83% when the data is noise-free audio, noisy audio, noise-free textual narratives, and noisy textual narratives, respectively.
机译:EMS(紧急医疗服务)在储蓄在紧急情况和事故情况下挽救生命起着重要作用。当第一个响应者包括EMS提供者和消防员,他们到达事件时,他们与患者(如果有意识),家庭成员和其他证人,其他第一响应者和指挥中度沟通。第一个响应者利用麦克风和耳机来支持这些通信。事件发生后,首批响应者必须通过填写表格来记录事件。今天,这是手动执行的。手动文档患者摘要报告是耗时,乏味和容易出错的。我们通过从场景转录音频来解决这些表单填充问题,从而识别来自所有对话的相关信息,并自动填写表格。对第一响应者的非正式调查表明,本申请对他们非常有帮助。结果表明,当数据不受无噪声音频,嘈杂的音频,无噪声文本叙述时,我们可以填写一个模型摘要报告表格,其F1分数高达94%,78%,96%和83%,并且嘈杂的文本叙述。

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