The AI Doctor Is In: A Survey of Task-Oriented Dialogue Systems for Healthcare Applications
The AI Doctor Is In: A Survey of Task-Oriented Dialogue Systems for Healthcare Applications
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DOI：
10.18653/v1/2022.acl-long.458
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
Mohammad Valizadeh;Natalie Parde
中科院分区：
文献类型：
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作者：
Mohammad Valizadeh;Natalie Parde
面向任务的对话系统在医疗环境中越来越普遍，并且具有多种架构和目标的特征。虽然这些系统已经在医学界从非技术的角度进行了调查，但从严格的计算角度进行的系统性审查迄今为止仍然明显缺乏。因此，面向医疗保健的对话系统的许多重要实施细节仍然有限或不够具体，减缓了这一领域的创新步伐。为了填补这一空白，我们调查了来自知名计算机科学、自然语言处理和人工智能领域的4070篇论文，确定了70篇讨论面向任务的对话系统在医疗保健应用中的系统级实现的论文。我们对这些论文进行了全面的技术审查，并提出了我们的主要发现，包括确定的差距和相应的建议。
Task-oriented dialogue systems are increasingly prevalent in healthcare settings, and have been characterized by a diverse range of architectures and objectives. Although these systems have been surveyed in the medical community from a non-technical perspective, a systematic review from a rigorous computational perspective has to date remained noticeably absent. As a result, many important implementation details of healthcare-oriented dialogue systems remain limited or underspecified, slowing the pace of innovation in this area. To fill this gap, we investigated an initial pool of 4070 papers from well-known computer science, natural language processing, and artificial intelligence venues, identifying 70 papers discussing the system-level implementation of task-oriented dialogue systems for healthcare applications. We conducted a comprehensive technical review of these papers, and present our key findings including identified gaps and corresponding recommendations.