Hybrid Personal Medical Digital Assistant Agents
Montagna S, Sirocchi C (2024)
Publication Language: English
Publication Type: Conference contribution, Original article
Publication year: 2024
Publisher: CEUR Workshop Proceedings
Series: Proceedings of the 25th Workshop "From Objects to Agents"
City/Town: Aachen
Book Volume: 3735
Pages Range: 58-72
Conference Proceedings Title: Hybrid Personal Medical Digital Assistant Agents
Event location: Bard
URI: https://ceur-ws.org/Vol-3735/paper_05.pdf
Open Access Link: https://ceur-ws.org/Vol-3735/paper_05.pdf
Abstract
Autonomous intelligent systems are beginning to impact clinical practice as personal medical assistant
agents, by leveraging experts’ knowledge when needed and exploiting the vast amount of patient data
available to clinicians. However, these approaches are seldom integrated. In this paper, we propose an
integrated hybrid agent architecture that combines symbolic reasoning with sub-symbolic, data-driven
models. Using the PIMA dataset, we demonstrate that this hybrid approach enhances the performance
of both approaches when used alone. Specifically, we show that integrating a logical agent, which uses
predefined expert knowledge plans, with rules obtained by symbolic knowledge extraction from machine
learning models trained on historical data, improves system reliability and clinical decision-making,
while reducing misclassified instances.
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How to cite
APA:
Montagna, S., & Sirocchi, C. (2024). Hybrid Personal Medical Digital Assistant Agents. In Marco Alderighi, Matteo Baldoni, Cristina Baroglio, Roberto Micalizio, Stefano Tedeschi (Eds.), Hybrid Personal Medical Digital Assistant Agents (pp. 58-72). Bard, IT: Aachen: CEUR Workshop Proceedings.
MLA:
Montagna, Sara, and Christel Sirocchi. "Hybrid Personal Medical Digital Assistant Agents." Proceedings of the 25th Workshop "From Objects to Agents", WOA 2024, Bard Ed. Marco Alderighi, Matteo Baldoni, Cristina Baroglio, Roberto Micalizio, Stefano Tedeschi, Aachen: CEUR Workshop Proceedings, 2024. 58-72.
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