Evidence map›Paper›PMID 35371617›Full record

ArticleProceedings. IEEE International Conference on Bioinformatics and Biomedicine2021

Dental EHR-infused Persona Ontologies to Enrich Dental Dialogue Interaction of Agents.

Patricia Ngantcha, Muhammad Tuan Amith, Kirk Roberts, John A Valenza, Muhammad Walji, Cui Tao

Abstract read
In one paragraph

Article in Proceedings. IEEE International Conference on Bioinformatics and Biomedicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Patricia NgantchaTexas Southern University, Houston, TX, USA.
Muhammad Tuan AmithSchool of Biomedical Informatics, University of Texas Health, Science Center at Houston, Houston, TX, USA.
Kirk RobertsSchool of Biomedical Informatics, University of Texas Health, Science Center at Houston, Houston, TX, USA.
John A ValenzaSchool of Dentistry, University of Texas Health, Science Center at Houston, Houston, TX, USA.
Muhammad WaljiSchool of Dentistry, University of Texas Health, Science Center at Houston, Houston, TX, USA.
Cui TaoSchool of Biomedical Informatics, University of Texas Health, Science Center at Houston, Houston, TX, USA.

Funding

Dynamic learning for post-vaccine event prediction using temporal information in VAERSR01AI130460 · NIAID · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI CHEN, YONG, TAO, CUI · 2017 to 2021
$3.4M
Natural Language Question Understanding for Electronic Health RecordsR00LM012104 · NLM · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI ROBERTS, KIRK EDWARD · 2016 to 2018
$747k
NIAID NIH HHS R01 AI130460NLM NIH HHS R00 LM012104
6 · The paper itself

Abstract

The quality of patient-provider communication can predict the healthcare outcomes in patients, and therefore, training dental providers to handle the communication effort with patients is crucial. In our previous work, we developed an ontology model that can standardize and represent patient-provider communication, which can later be integrated in conversational agents as tools for dental communication training. In this study, we embark on enriching our previous model with an ontology of patient personas to portray and express types of dental patient archetypes. The Ontology of Patient Personas that we developed was rooted in terminologies from an OBO Foundry ontology and dental electronic health record data elements. We discuss how this ontology aims to enhance the aforementioned dialogue ontology and future direction in executing our model in software agents to train dental students.

Indexed as

biomedical informaticseducational technologyelectronic medical recordsintelligent agentknowledge representationsemantic web

Identifiers

PMID35371617
PMCPMC8972912

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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.