Automated classification of coronary atherosclerosis using single lead ECG

2013 IEEE Conference on Wireless Sensor, ICWISE 2013

Volumn , Issue , 2013, Pages 108-113

  Kaveh, Anthony ^a   Chung, Wayne ^b  

^a STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b Wireless Medical Monitoring Inc   (United States)

Author keywords

atherosclerosis; coronary heart disease; ECG; electrocardiogram; machine learning; SVM

Indexed keywords

BLOOD VESSELS; DIAGNOSIS; ELECTROCARDIOGRAPHY; LEARNING SYSTEMS; SENSORS;

ATHEROSCLEROSIS; AUTOMATED CLASSIFICATION; CLASSIFICATION METHODS; CORONARY HEART DISEASE; DIAGNOSTIC PERFORMANCE; ELECTRODE PLACEMENT; SENSOR IMPLEMENTATION; SVM;

DISEASES;

EID: 84894122072     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICWISE.2013.6728790     Document Type: Conference Paper

References (45)

1. 1 J. Strong, G. Malcom, C. McMahan, R. Tracy, W. Newman 3rd, E. Herderick, J. Cornhill. Prevalence and extent of atherosclerosis in adolescents and young adults: implications for prevention from the Pathobiological Determinants of Atherosclerosis in Youth Study. JAMA 1999;281:727.
2. 1 C. Murray, A. Lopez. "Mortality by cause for eight regions of the world: Global Burden of Disease Study." The Lancet 349. 9061(1997):1269-1276. (Pubitemid 27192468)
3. 1 P. Greenland, J. Gaziano. Clinical practice. Selecting asymptomatic patients for coronary computed tomography or electrocardiographic exercise testing. N Engl J Med 2003;349:465.
4. 1 D. Lerner, W. Kannel. Patterns of coronary heart disease morbidity and mortality in the sexes: a 26-year follow-up of the Framingham population. Am Heart J 1986;111:383.
5. 1 P. Greenland, J. Gaziano. Clinical practice. Selecting asymptomatic patients for coronary computed tomography or electrocardiographic exercise testing. N Engl J Med 2003;349:465.
6. 1 P. Rautaharju, R. Prineas, W. Eifler, C. Furberg, J. Neaton, R. Crow, J. Stamler, J. Cutler. "Prognostic value of exercise electrocardiogram in men at high risk of future coronary heart disease: Multiple Risk Factor Intervention Trial experience." Journal of the American College of Cardiology 8, no. 1(1986):1-10. (Pubitemid 16094106)
7. 1 V. Roger, S. Jacobsen, P. Pellikka, T. Miller, K. Bailey, B. Gersh. Prognostic value of treadmill exercise testing: a population-based study in Olmsted County, Minnesota. Circulation 1998;98:2836.
8. 1 G. Diamond, M. Hirsch, J. Forrester, H. Staniloff, R. Vas, S. Halpern, H. Swan. Application of information theory to clinical diagnostic testing. The electrocardiographic stress test. Circulation 1981;63:915.
9. 1 R. Califf, P. Armstrong, J. Carver, R. D'Agostino, W. Strauss. 27th Bethesda Conference: matching the intensity of risk factor management with the hazard for coronary disease events. Task Force 5. Stratification of patients into high, medium and low risk subgroups for purposes of risk factor management. J Am Coll Cardiol 1996;27:1007.
10. 1 H. Sox, B. Littenberg, A. Garber. The role of exercise testing in screening for coronary artery disease. Ann Intern Med 1989;110:456.
11. 1 M. Daviglus, Y. Liao, P. Greenland, A. Dyer, K. Liu, X. Xie, C. Huang, R. Prineas, J. Stamler. Association of nonspecific minor ST-T abnormalities with cardiovascular mortality: the Chicago Western Electric Study. JAMA 1999;281:530.
12. 1 D. De Bacquer, G. De Backer, M. Kornitzer, K. Myny, Z. Doyen, H. Blackburn. Prognostic value of ischemic electrocardiographic findings for cardiovascular mortality in men and women. J Am Coll Cardiol 1998;32:680.
13. 1 Coronary artery surgery study (CASS): a randomized trial of coronary artery bypass surgery. Survival data. Circulation 1983;68:939.
14. 1 G. Rose, P. Baxter, D. Reid, P. McCartney. Prevalence and prognosis of electrocardiographic findings in middle-aged men. Br Heart J 1978;40:636.
15. 1 J. Mahmarian, R. Steingart, S. Forman, B. Sharaf, M. Coglianese, D. Miller, C. Pepine, A. Goldberg, M. Bloom, S. Byers, L. Dvorak, C. Pratt. Relation between ambulatory electrocardiographic monitoring and myocardial perfusion imaging to detect coronary artery disease and myocardial ischemia: an ACIP ancillary study. The Asymptomatic Cardiac Ischemia Pilot (ACIP) Investigators. J Am Coll Cardiol 1997;29:764.
16. 1 D. Dubin. Rapid interpretation of EKG's: an interactive course. Cover Publishing Company, 2000.
17. 1 M. Bots, M. Breteler, A. Hofman, D. Grobbee, J van Swieten, J. van Gijn, P. de Jong. "Cerebral white matter lesions and atherosclerosis in the Rotterdam Study." The Lancet 341, no. 8855(1993):1232-1237. (Pubitemid 23146928)
18. 1 H. Blackburn, A. Keys, E. Simonson, P. Rautaharju, S. Punsar. "The electrocardiogram in population studies: a classification system." Circulation 21, no. 6(1960):1160-1175.
19. A. Reunanen, K. Pyörälä, SPunsar S, A. Aromaa. Predictive value of ECG findings with respect to coronary heart disease mortality. Adv Cardiol 1978;21:310-2.
20. 1 H. Blackburn, H. Taylor, A. Keys. The electrocardiogram in prediction of five-year coronary heart disease incidence among men aged 40 through 59. Circulation 1970;42(suppl):154-61.
21. 1 D. De Bacquer, G. De Backer, M. Kornitzer. "Prevalences of ECG findings in large population based samples of men and women. " Heart 84. 6(2000):625-633.
22. 1 L. Vitelli, R. Crow, E. Shahar, R. Hutchinson, P. Rautaharju, A. Folsom. "Electrocardiographic findings in a healthy biracial population. Atherosclerosis Risk in Communities (ARIC) Study Investigators." The American journal of cardiology 81, no. 4(1998):453.
23. 1 S. Hernberg, R. Kärävä, RS. Koskela, K. Luoma. "Angina pectoris, ECG findings and blood pressure of foundry workers in relation to carbon monoxide exposure." Scandinavian journal of work, environment & health (1976):54-63.
24. 1 A. Salem, K. Revett, E. El-Dahshan. "Machine learning in electrocardiogram diagnosis." Computer Science and Information Technology, 2009. IMCSIT'09. International Multiconference on. IEEE, 2009.
25. 1 Vapnik, V. Statistical Learning Theory. Wiley, New York, 1998.
26. 1 KN. Plataniotis, D. Hatzinakos, JK Lee. "ECG biometric recognition without fiducial detection. " Biometric Consortium Conference, 2006 Biometrics Symposium: Special Session on Research at the. IEEE, 2006.
27. 1 S. Mehta, N Lingayat. "Identification of QRS complexes in 12-lead electrocardiogram." Expert Systems with Applications 36. 1(2009):820-828.
28. 1 B. Asl, S. Setarehdan, M. Mohebbi. "Support vector machine-based arrhythmia classification using reduced features of heart rate variability signal." Artificial intelligence in medicine 44, no. 1(2008):51-64.
29. 1C. Li, C. Zheng, C. Tai. "Detection of ECG characteristic points using wavelet transforms." Biomedical Engineering, IEEE Transactions on 42. 1(1995):21-28.
30. 1 JP. Martínez, R. Almeida, S. Olmos, AP. Rocha, P. Laguna. (2004). A wavelet-based ECG delineator: evaluation on standard databases. Biomedical Engineering IEEE Transactions on, 51(4), 570-581. (Pubitemid 38375132)
31. 1 A. Cohen and J. Kovačević, "Wavelets: The mathematical background", Proc. IEEE, vol. 84, pp. 514-522, Apr. 1996. (Pubitemid 126752548)
32. 1 NV. Boulgouris, KN. Plataniotis, E. Micheli-Tzanakou. (2009). Biometrics: theory, methods, and applications (Vol. 9). Wiley-IEEE Press.
33. 1 S. Hunt, D. Baker, M. Chin, M. Cinquegrani, A. Feldmanmd, et al. "ACC/AHA guidelines for the evaluation and management of chronic heart failure in the adult: executive summary a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Committee to Revise the 1995 Guidelines for the Evaluation and Management of Heart Failure)." Circulation 104, no. 24(2001):2996-3007. (Pubitemid 33139116)
34. 1 J. Kanaley, T. Baynard, R Franklin, R. Weinstock, S. Goulopoulou, R Carhart, R Ploutz-Snyder, A. Figueroa, B. Fernhall. "The effects of a glucose load and sympathetic challenge on autonomic function in obese women with and without type 2 diabetes." Metabolism: clinical and experimental 56, no. 6(2007):778.
35. 1 P. Welch. "The use of fast Fourier transform for the estimation of power spectra: a method based on time averaging over short, modified periodograms." Audio and Electroacoustics, IEEE Transactions on 15. 2(1967):70-73.
36. 1 C. Cortes, V. Vapnik "Support-vector networks." Machine learning 20. 3(1995):273-297.
37. 1 B. Wallace, I. Dahabreh. "Class Probability Estimates are Unreliable for Imbalanced Data (and How to Fix Them)." Data Mining (ICDM), 2012 IEEE 12th International Conference on. IEEE, 2012.
38. 1 J. Swets. Signal detection theory and ROC analysis in psychology and diagnostics: collected papers, Lawrence Erlbaum Associates, Mahwah, NJ 1996
39. 1 AL. Goldberger, LAN. Amaral, L. Glass, JM. Hausdorff, PCh. Ivanov, RG. Mark, JE. Mietus, GB. Moody, CK Peng, HE. Stanley. PhysioBank, PhysioToolkit, and PhysioNet: Components of a New Research Resource for Complex Physiologic Signals. Circulation 101(23):e215-e220.
40. 1 F. Jousset, M. Lemay, J. Vesin. "Computers in cardiology/physioNet challenge 2009: Predicting acute hypotensive episodes." Computers in Cardiology, 2009. IEEE, 2009.
41. 1 B. Asl, S. Kamaledin, M. Mohebbi. "Support vector machine-based arrhythmia classification using reduced features of heart rate variability signal." Artificial intelligence in medicine 44. 1(2008):51-64.
42. 1 H. Chen, F. Zeng, K. Tseng, H. Huang, S. Tu, J. Panl. (2012, July). ECG Human Identification with Statistical Support Vector Machines. In Computing, Measurement, Control and Sensor Network (CMCSN), 2012 International Conference on (pp. 237-240). IEEE.
43. 1 C. Chang, C. Lin. LIBSVM: a library for support vector machines. ACM Transactions on Intelligent Systems and Technology, 2:27: 1-27:27, 2011. http://www.csie.ntu.edu.tw/~cjlin/libsvm
44. 1 N. Chawla, N. Japkowicz, A. Kotcz. "Editorial: special issue on learning from imbalanced data sets." ACM SIGKDD Explorations Newsletter 6. 1(2004):1-6.
45. 1 J. Bazan, S. Bazan-Socha, S. Buregwa-Czuma, P. Wiktor Pardel, B. Sokolowska. "Prediction of coronary arteriosclerosis in stable coronary heart disease." In Advances in Computational Intelligence, pp. 550-559 Springer Berlin Heidelberg, 2012.