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Integrating Different Methodologies for Insulin Therapy Support in Type 1 Diabetic Patients

  • Stefania Montani
  • Paolo Magni
  • Abdul V. Roudsari
  • Ewart R. Carson
  • Riccardo Bellazzi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2101)

Abstract

We propose a Multi Modal Reasoning (MMR) methodology designed to provide physicians with knowledge management and decision support functionality in the context of type 1 diabetes melli tus care. The MMR system performs a tight integration of Case Based Reasoning (CBR), Rule Based Reasoning (RBR) and Model Based Reasoning (MBR), with the aim of suggesting a therapy properly tailored to the patient’s needs, overcoming the single approaches’ limitations. This methodology allows the exploitation of the implicit knowledge embedded in patients’ visits (past cases) and in monitoring data through Case Based retrieval. Moreover the explicit domain knowledge is formalized in a set of production rules and in a mathematical model. The system has been preliminary tested both on simulated and on real patients’ data.

Keywords

Blood Glucose Level Case Base Reasoning Intensive Insulin Therapy Case Library Past Case 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Stefania Montani
    • 1
  • Paolo Magni
    • 1
  • Abdul V. Roudsari
    • 2
  • Ewart R. Carson
    • 2
  • Riccardo Bellazzi
    • 1
  1. 1.Dipartimento di Informatica e Sistemistica Università di PaviaPaviaItaly
  2. 2.MIM CenterCity UniversityUK

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