Analysis of support vectors helps to identify borderline patients in classification studies

Computers in Cardiology

Volumn 29, Issue , 2002, Pages 305-308

  Schwenker, Friedhelm ^a   Kestler, H A ^a,b  

^a UNIVERSITY OF ULM   (Germany)

^b UNIVERSITY HOSPITAL ULM   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); COMPUTER AIDED DIAGNOSIS; MEDICAL COMPUTING; METADATA; OPTIMIZATION; PATIENT MONITORING;

SUPPORT VECTOR MACHINES (SVM);

ELECTROCARDIOGRAPHY;

EID: 0036955666     PISSN: 02766574     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (14)

1. Simson M. Use of Signals in the Terminal QRS Complex to Identify Patients with Ventricular Tachycardia after Myocardial Infarction. Circulation 1981;64(2):235-242.
2. Gomes J, Winters S, Martinson M, Machac J, Stewart D, Targonski A. The prognostic significance of quantitative signal-averaged variables relative to clinical variables, site of myocardial infarction, ejection fraction and ventricular premature beats. JACC 1989;13:377-384.
3. Höher M, Hombach V. Ventrikuläre Spätpotentiale - Teil I Grundlagen. Herz Rhythmus 1991;3(3):1-7.
4. Höher M, Hombach V. Ventrikuläre Spätpotentiale - Teil II Klinische Aspekte. Herz Rhythmus 1991;3(4):8-14.
5. Breithardt G, Borggrefe M. Pathophysiological mechanisms and clinical significance of ventricular late potentials. Eur Heart J 1986;7:364-385.
6. Breithardt G, Cain M, El-Sherif N, Flowers N, Hombach V, Janse M, Simson M, Steinbeck G. Standards for analysis of ventricular late potentials using high resolution or signal-averaged electrocardiography. Eur Heart J 1991; 12:473-80.
7. Rosenbaum D, Jackson L, Smith L, Garan H, Ruskin J, Cohen R. Electrical alternans and vulnerability to ventricular arrhythmias. N Engl J Med 1994;330(4):235-41.
8. Kestler HA, Wöhrle J, Höher M. Cardiac vulnerability assessment from electrical microvariability of the high-resolution electrocardiogram. Medical Biological Engineering Computing 2000;38:88-92.
9. Cortes C, Vapnik V. Support vector networks. Machine Learning 1995;20:273-297.
10. Schölkopf A, Burges C, Smola A. Advances in Kernel Methods - Support Vector Learning. MIT Press, 1998.
11. Vapnik V. Statistical Learning Theory. John Wiley and Sons, 1998.
12. Ritscher D, Ernst E, Kammrath H, Hombach V, Höher M. High-resolution ecg analysis platform with enhanced resolution. Computers in Cardiology 1997;24:291-94.
13. van Bemmel J, Musen M (eds.). Handbook of Medical Informatiks. Springer Verlag, 1997.
14. de Boor C. A Practical Guide to Splines. Springer Verlag, 1978.