Exploiting expert systems in cardiology: a comparative study

Adv Exp Med Biol. 2015:820:79-89. doi: 10.1007/978-3-319-09012-2_6.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cardiology / methods*
  • Cardiovascular Diseases / diagnosis*
  • Expert Systems*
  • Fuzzy Logic*
  • Humans
  • Neural Networks, Computer*
  • Reproducibility of Results
  • Sensitivity and Specificity