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dc.contributor.author IAPASCURTA, Victor
dc.contributor.author FIODOROV, Ion
dc.contributor.author BELII, Adrian
dc.contributor.author BOSTAN, Viorel
dc.date.accessioned 2025-07-16T12:02:04Z
dc.date.available 2025-07-16T12:02:04Z
dc.date.issued 2025
dc.identifier.citation IAPASCURTA, Victor; Ion FIODOROV; Adrian BELII and Viorel BOSTAN. Multi-agent approach for sepsis management. Healthcare Informatics Research. 2025, vol. 31, nr. 2, pp. 209-214. ISSN 20933-681. en_US
dc.identifier.issn 20933-681
dc.identifier.uri https://doi.org/10.4258/hir.2025.31.2.209
dc.identifier.uri https://repository.utm.md/handle/5014/32833
dc.description Access full text: https://doi.org/10.4258/hir.2025.31.2.209 en_US
dc.description.abstract Objectives: The high incidence of sepsis necessitates the development of practical decision-making tools for intensivists, especially during the early, critical phases of management. This study evaluates a multi-agent system intended to assist clinicians with antibiotic therapy and adherence to current sepsis management guidelines before diagnostic results become avail-able. Methods: A multi-agent system incorporating three specialized agents was developed: a sepsis management agent, an antibiotic recommendation agent, and a sepsis guidelines compliance agent. A sepsis case from the MIMIC IV database, organized as a clinical vignette, was used to integrate and test these agents for generating management recommendations. The system leverages retrieval-augmented generation to improve decision-making through the integration of current literature and guidelines. Results: The application produced management recommendations for a sepsis case associated with pneumonia, including early initiation of broad-spectrum antibiotics and close monitoring for clinical deterioration. Two expert intensivists evaluated these recommendations as “acceptable” and reported moderate interrater agreement (Cohen’s kappa = 0.622, p = 0.003) across various aspects of recommendation usefulness. Conclusions: The multi-agent system shows promise in enhancing decision-making for sepsis management by optimizing antibiotic therapy and ensuring guideline compliance. However, reliance on a single case study limits the generalizability of the findings, highlighting the need for broader validation in diverse clinical settings to improve patient outcomes. en_US
dc.language.iso en en_US
dc.publisher Korean Society of Medical Informatics en_US
dc.rights Attribution-NonCommercial-NoDerivs 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/us/ *
dc.subject sepsis en_US
dc.subject decision support systems en_US
dc.subject clinical en_US
dc.subject medical informatics applications en_US
dc.subject critical care en_US
dc.subject artificial intelligence en_US
dc.title Multi-agent approach for sepsis management en_US
dc.type Article en_US


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