Abstract
The interest towards spoken dialogue systems has been rapidly growing in the last few years, including the field of health care. There is a growing need for automated systems that can do more than order airline and movie tickets, find restaurants and hotels, or find information on the internet. Eliciting information from patients about their current health and medications using natural language at the point of care is a task currently performed by skilled nurses during the intake interview in both inpatient and outpatient settings. This routine task lends itself well to automation and a well-crafted dialogue system with state management can enable standardized yet individually tailored interactions with the patient using natural language. The need for extensive domain knowledge (e.g. medications, dosages, disorders, symptoms, etc.) in order to achieve broad coverage makes this task particularly challenging. In this project, we explore the use of the PyDial framework and a medication-oriented knowledge base containing information from RxNorm to create a dialogue system capable of eliciting medication history information from patients.
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Work supported in part by CRA-W Distributed Research Experiences for Undergraduates program.
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Zheng, J., Finzel, R., Pakhomov, S., Gini, M. (2020). Spoken Dialogue Systems for Medication Management. In: Shaban-Nejad, A., Michalowski, M. (eds) Precision Health and Medicine. W3PHAI 2019. Studies in Computational Intelligence, vol 843. Springer, Cham. https://doi.org/10.1007/978-3-030-24409-5_11
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DOI: https://doi.org/10.1007/978-3-030-24409-5_11
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