title: Exploiting expert systems in cardiology: a comparative study.
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.affiliation: Department of Computer Science, Hellenic Open University, 26335, Patras, Greece, econom@upatras.gr.
authors.forename: George-Peter K
authors.initials: GP
authors.lastname: Economou
authors.forename: Efrosini
authors.initials: E
authors.lastname: Sourla
authors.forename: Konstantina-Maria
authors.initials: KM
authors.lastname: Stamatopoulou
authors.forename: Vasileios
authors.initials: V
authors.lastname: Syrimpeis
authors.forename: Spyros
authors.initials: S
authors.lastname: Sioutas
authors.forename: Athanasios
authors.initials: A
authors.lastname: Tsakalidis
authors.forename: Giannis
authors.initials: G
authors.lastname: Tzimas
mesh_terms: D002309:Cardiology / Q000379:methods*; D002318:Cardiovascular Diseases / Q000175:diagnosis*; D005103:Expert Systems; D017143:Fuzzy Logic; D006801:Humans; D016571:Neural Networks, Computer; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity