| 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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