Exploiting expert systems in cardiology: a comparative study.

Journal: Advances in experimental medicine and biology
Published Date:

Abstract

An improved Adaptive Neuro-Fuzzy Inference System (ANFIS) in the field of critical cardiovascular diseases is presented. The system stems from an earlier application based only on a Sugeno-type Fuzzy Expert System (FES) with the addition of an Artificial Neural Network (ANN) computational structure. Thus, inherent characteristics of ANNs, along with the human-like knowledge representation of fuzzy systems are integrated. The ANFIS has been utilized into building five different sub-systems, distinctly covering Coronary Disease, Hypertension, Atrial Fibrillation, Heart Failure, and Diabetes, hence aiding doctors of medicine (MDs), guide trainees, and encourage medical experts in their diagnoses centering a wide range of Cardiology. The Fuzzy Rules have been trimmed down and the ANNs have been optimized in order to focus into each particular disease and produce results ready-to-be applied to real-world patients.

Authors

  • George-Peter K Economou
    Department of Computer Science, Hellenic Open University, 26335, Patras, Greece, econom@upatras.gr.
  • Efrosini Sourla
  • Konstantina-Maria Stamatopoulou
  • Vasileios Syrimpeis
  • Spyros Sioutas
  • Athanasios Tsakalidis
  • Giannis Tzimas