Exploiting Expert Systems in Cardiology: A Comparative Study
| Autor: | George-Peter K. Economou, Efrosini Sourla, Spyros Sioutas, Konstantina-Maria Stamatopoulou, Athanasios K. Tsakalidis, Giannis Tzimas, Vasileios Syrimpeis |
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| Rok vydání: | 2014 |
| Předmět: |
medicine.medical_specialty
Adaptive neuro fuzzy inference system Knowledge representation and reasoning Artificial neural network business.industry Fuzzy control system computer.software_genre Fuzzy logic Expert system Field (computer science) Internal medicine Cardiology medicine Medical diagnosis business computer |
| Zdroj: | Advances in Experimental Medicine and Biology ISBN: 9783319090115 |
| DOI: | 10.1007/978-3-319-09012-2_6 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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