Conversational Assistants to support Heart Failure Patients: comparing a Neurosymbolic Architecture with ChatGPT

• URL: http://arxiv.org/abs/2504.17753v1
• Date: Thu, 24 Apr 2025 17:16:24 GMT
• Title: Conversational Assistants to support Heart Failure Patients: comparing a Neurosymbolic Architecture with ChatGPT
• Authors: Anuja Tayal, Devika Salunke, Barbara Di Eugenio, Paula Allen-Meares, Eulalia Puig Abril, Olga Garcia, Carolyn Dickens, Andrew Boyd,
• Abstract summary: We compare two versions of a conversational assistant that allows heart failure patients to ask about salt content in food.<n>One version was developed in-house with a neurosymbolic architecture, and one is based on ChatGPT.<n>The evaluation shows that the in-house system is more accurate, completes more tasks and is less verbose than the one based on ChatGPT.
• Score: 0.7334873346655889
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Conversational assistants are becoming more and more popular, including in healthcare, partly because of the availability and capabilities of Large Language Models. There is a need for controlled, probing evaluations with real stakeholders which can highlight advantages and disadvantages of more traditional architectures and those based on generative AI. We present a within-group user study to compare two versions of a conversational assistant that allows heart failure patients to ask about salt content in food. One version of the system was developed in-house with a neurosymbolic architecture, and one is based on ChatGPT. The evaluation shows that the in-house system is more accurate, completes more tasks and is less verbose than the one based on ChatGPT; on the other hand, the one based on ChatGPT makes fewer speech errors and requires fewer clarifications to complete the task. Patients show no preference for one over the other.

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