Erratum "Assessment of exercise stress testing with artificial neural network in determining coronary artery disease and predicting lesion localization" [Experts Systems with Applications 36 (2P1) (2009) 2562-2566] (DOI:10.1016/j.eswa.2007.11.013);Assessment of exercise stress testing with artificial neural network in determining coronary artery disease and predicting lesion localization

Expert Systems with Applications

Volumn 36, Issue 2 PART 1, 2009, Pages 2562-2566

  Babaoglu, Ismail ^a   Baykan, Omer Kaan ^a   Aygul, Nazif ^a   Ozdemir, Kurtulus ^a   Bayrak, Mehmet ^a  

^a SELCUK UNIVERSITY   (Turkey)

Author keywords

Artificial neural networks; Coronary artery disease; Exercise stress testing

Indexed keywords

BLOOD VESSELS; DIAGNOSIS; HEART; NETWORK LAYERS; NEURAL NETWORKS;

10-FOLD CROSS-VALIDATION; CORONARY ARTERY DISEASE; EXERCISE STRESS TESTING; LEFT ANTERIOR DESCENDING; LOCALIZATION OF LESIONS; MULTI-LAYERED PERCEPTRON; NEGATIVE PREDICTIVE VALUE; RIGHT CORONARY ARTERY;

DISEASES;

EID: 56349166799     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2009.07.002     Document Type: Erratum

References (17)

1. Ceylan M., Ceylan R., Dirgenali F., Kara S., and Ozbay Y. Classification of carotid artery Doppler signals in the early phase of atherosclerosis using complex-valued artificial neural network. Computers in Biology and Medicine 37 (2007) 28-36
2. Chauhan A., Thuraisingham S.I., and Stone D.L. Exercise electrocardiogram and single vessel coronary artery disease. Postgraduate Medical Journal 73 (1997) 655-657
3. Comak E., Arslan A., and Turkoglu I. A decision support system based on support vector machines for diagnosis of the heart valve diseases. Computers in Biology and Medicine 37 (2007) 21-27
4. De Castro L.N., and Timmis J. Artificial immune systems: A new computational intelligence approach (2002), Springer-Verlag
5. Delen D., Walker G., and Kadam A. Predicting breast cancer survivability: A comparison of three data mining methods. Artificial Intelligence in Medicine 34 (2005) 113-127
6. Gallik D.M., Mahmarian J.J., and Verani M.S. Therapeutic significance of exercise-induced ST-segment elevation in patients without previous myocardial infarction. American Journal of Cardiology 72 (1993) 1-7
7. Gates T.J. Screening for cancer: Evaluating the evidence. American Family Physician 63 3 (2001) 513-522
8. Gibbons, R. J., Balady, G. J., Bricker, J. T., et al. (2002). ACC/AHA 2002 guideline update for exercise testing: Summary article. A report of the american college of cardiology/american heart association task force on practice guidelines (committee to update the 1997 exercise testing guidelines). Journal of the American College of Cardiology, 40, 1531-1540.
9. Guler I., and Ubeyli E.D. ECG beat classifier designed by combined neural network model. Pattern Recognition 38 2 (2005) 199-208
10. Kannathal N., Lim C.M., Rajendra Acharya U., and Sadasivan P.K. Cardiac state diagnosis using adaptive neuro-fuzzy technique. Medical Engineering and Physics 28 8 (2006) 809-815
11. Nielsen C., and Lang R.S. Principles of screening. The Medical Clinics of North America 83 6 (1999) 1323-1337
12. Ozbay Y., Ceylan R., and Karlik B. A fuzzy clustering neural network architecture for classification of ECG arrhythmias. Computers in Biology and Medicine 36 4 (2006) 376-388
13. Pao Y.H. Adaptive pattern recognition and neural networks (1989), Addison-Wesley, Reading
14. Polat K., Sahan S., and Gunes S. A new method to medical diagnosis: Artificial immune recognition system (AIRS) with fuzzy weighted pre-processing and application to ECG arrhythmia. Expert Systems with Applications 31 2 (2006) 264-269
15. San Roman J.A., Vilacosta I., Castillo J.A., et al. Selection of the optimal stress test for the diagnosis of coronary artery disease. Heart 80 (1998) 370-376
16. Serhatlioglu S., Hardalac F., and Guler I. Classification of transcranial doppler signals using artificial neural network. Journal of Medical Systems 27 (2003) 205-214
17. Turkoglu I., Arslan A., and Ilkay E. An expert system for diagnosis of the heart valve diseases. Expert Systems with Applications 23 3 (2002) 229-236