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Erschienen in:
2013 | OriginalPaper | Buchkapitel
A Multi-agent Planning Approach for the Generation of Personalized Treatment Plans of Comorbid Patients
verfasst von : Inmaculada Sánchez-Garzón, Juan Fdez-Olivares, Eva Onaindía, Gonzalo Milla, Jaume Jordán, Pablo Castejón
Erschienen in: Artificial Intelligence in Medicine
Verlag: Springer Berlin Heidelberg
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This work addresses the generation of a personalized treatment plan from multiple clinical guidelines, for a patient with multiple diseases (comorbid patient), as a multi-agent cooperative planning process that provides support to collaborative medical decision-making. The proposal is based on a multi-agent planning architecture in which each agent is capable of (1) planning a personalized treatment from a temporal Hierarchical Task Network (HTN) representation of a single-disease guideline, and (2) coordinating with other planning agents by both sharing disease specific knowledge, and resolving the eventual conflicts that may arise when conciliating different guidelines by merging single-disease treatment plans. The architecture follows a life cycle that starting from a common specification of the main high-level steps of a treatment for a given comorbid patient, results in a detailed treatment plan without harmful interactions among the single-disease personalized treatments.