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A Multi-agent Planning Approach for the Generation of Personalized Treatment Plans of Comorbid Patients

  • Inmaculada Sánchez-Garzón
  • Juan Fdez-Olivares
  • Eva Onaindía
  • Gonzalo Milla
  • Jaume Jordán
  • Pablo Castejón
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7885)

Abstract

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.

Keywords

multi-agent planning comorbidity guideline conciliation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Inmaculada Sánchez-Garzón
    • 1
  • Juan Fdez-Olivares
    • 1
  • Eva Onaindía
    • 2
  • Gonzalo Milla
    • 1
  • Jaume Jordán
    • 2
  • Pablo Castejón
    • 2
  1. 1.Department of Computer Science and AIUniversidad de GranadaSpain
  2. 2.Department of Computer ScienceUniversitat Politècnica de ValènciaSpain

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