ArticleBMC medical informatics and decision making2020
Conversational ontology operator: patient-centric vaccine dialogue management engine for spoken conversational agents.
Article in BMC medical informatics and decision making, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- An application-based ontological knowledge base of medications to support health literacy and adherence for the consumer population: an aging population use case.Journal of biomedical semantics · 2026Article
- Computational tools and data integration to accelerate vaccine development: challenges, opportunities, and future directions.Frontiers in immunology · 2025Review
- An ontology-based method for formalizing and encoding patient colonoscopy preparation using BPMN and OWL2 for automated tool development.Journal of clinical informatics · 2025Article
- Translating motivational interviewing for the HPV vaccine into a computable ontology model for automated AI conversational interaction.Extended abstracts on Human factors in computing systems. CHI Conference · 2024Article
- Machine and cognitive intelligence for human health: systematic review.Brain informatics · 2022Review
- Patient-Provider Communication Training Models for Interactive Speech Devices.Digital human modeling and applications in health, safety, ergonomics and risk management : human body, motion and behavior : 12th International Conference, DHM 2021, held as part of the 23rd HCI International Conference, HCII 2021, Vir... · 2021Article
- Selected articles from the Fourth International Workshop on Semantics-Powered Data Mining and Analytics (SEPDA 2019).BMC medical informatics and decision making · 2020Article
- A health consumer ontology of fast food information.Proceedings. IEEE International Conference on Bioinformatics and Biomedicine · 2020Article
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Authors and funding
9 authors.
Funding
Abstract
backgroundPreviously, we introduced our Patient Health Information Dialogue Ontology (PHIDO) that manages the dialogue and contextual information of the session between an agent and a health consumer. In this study, we take the next step and introduce the Conversational Ontology Operator (COO), the software engine harnessing PHIDO. We also developed a question-answering subsystem called Frankenstein Ontology Question-Answering for User-centric Systems (FOQUS) to support the dialogue interaction.
methodsWe tested both the dialogue engine and the question-answering system using application-based competency questions and questions furnished from our previous Wizard of OZ simulation trials.
resultsOur results revealed that the dialogue engine is able to perform the core tasks of communicating health information and conversational flow. Inter-rater agreement and accuracy scores among four reviewers indicated perceived, acceptable responses to the questions asked by participants from the simulation studies, yet the composition of the responses was deemed mediocre by our evaluators.
conclusionsOverall, we present some preliminary evidence of a functioning ontology-based system to manage dialogue and consumer questions. Future plans for this work will involve deploying this system in a speech-enabled agent to assess its usage with potential health consumer users.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.