@inproceedings{valizadeh-parde-2022-ai,
title = "The {AI} Doctor Is In: A Survey of Task-Oriented Dialogue Systems for Healthcare Applications",
author = "Valizadeh, Mina and
Parde, Natalie",
editor = "Muresan, Smaranda and
Nakov, Preslav and
Villavicencio, Aline",
booktitle = "Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = may,
year = "2022",
address = "Dublin, Ireland",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.acl-long.458",
doi = "10.18653/v1/2022.acl-long.458",
pages = "6638--6660",
abstract = "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.",
}
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%0 Conference Proceedings
%T The AI Doctor Is In: A Survey of Task-Oriented Dialogue Systems for Healthcare Applications
%A Valizadeh, Mina
%A Parde, Natalie
%Y Muresan, Smaranda
%Y Nakov, Preslav
%Y Villavicencio, Aline
%S Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2022
%8 May
%I Association for Computational Linguistics
%C Dublin, Ireland
%F valizadeh-parde-2022-ai
%X 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.
%R 10.18653/v1/2022.acl-long.458
%U https://aclanthology.org/2022.acl-long.458
%U https://doi.org/10.18653/v1/2022.acl-long.458
%P 6638-6660
Markdown (Informal)
[The AI Doctor Is In: A Survey of Task-Oriented Dialogue Systems for Healthcare Applications](https://aclanthology.org/2022.acl-long.458) (Valizadeh & Parde, ACL 2022)
ACL