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首页> 外文会议>Workshop on Natural Language Processing for Medical Conversations >Classifying Electronic Consults for Triage Status and Question Type
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Classifying Electronic Consults for Triage Status and Question Type

机译：分类电子咨询分类状态和问题类型

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Electronic consult (eConsult) systems allow specialists more flexibility to respond to referrals more efficiently, thereby increasing access in under-resourced healthcare settings like safety net systems. Understanding the usage patterns of eConsult system is an important part of improving specialist efficiency. In this work, we develop and apply classifiers to a dataset of eConsult questions from primary care providers to specialists, classifying the messages for how they were triaged by the specialist office, and the underlying type of clinical question posed by the primary care provider. We show that pre-trained transformer models are strong baselines, with improving performance from domain-specific training and shared representations.
机译：电子咨询（eConsult）系统允许专家更灵活地响应推荐更有效，从而增加了资源欠资源保健设置的访问，如安全网系统。了解生态系统的使用模式是提高专业效率的重要组成部分。在这项工作中，我们开发并将分类器从初级护理提供商向专家中发出分类机，对专家，分类他们如何由专家办公室进行三层的信息，以及初级保健提供者提出的临床问题的潜在类型。我们表明，训练有素的变压器模型是强大的基线，具有从域特定培训和共享表示的性能。

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