125 related articles for article (PubMed ID: 11465892)
1. Radial basis function neural network approach for the diagnosis of coronary artery disease based on the standard electrocardiogram exercise test.
Lewenstein K
Med Biol Eng Comput; 2001 May; 39(3):362-7. PubMed ID: 11465892
[TBL] [Abstract][Full Text] [Related]
2. Prognostic value of heart rate adjustment of exercise-induced ST segment depression in the multiple risk factor intervention trial.
Okin PM; Grandits G; Rautaharju PM; Prineas RJ; Cohen JD; Crow RS; Kligfield P
J Am Coll Cardiol; 1996 May; 27(6):1437-43. PubMed ID: 8626955
[TBL] [Abstract][Full Text] [Related]
3. A consensus approach to diagnosing coronary artery disease based on clinical and exercise test data.
Do D; West JA; Morise A; Atwood E; Froelicher V
Chest; 1997 Jun; 111(6):1742-9. PubMed ID: 9187202
[TBL] [Abstract][Full Text] [Related]
4. An agreement approach to predict severe angiographic coronary artery disease with clinical and exercise test data.
Do D; West JA; Morise A; Atwood JE; Froelicher V
Am Heart J; 1997 Oct; 134(4):672-9. PubMed ID: 9351734
[TBL] [Abstract][Full Text] [Related]
5. Electrocardiogram signal variance analysis in the diagnosis of coronary artery disease--a comparison with exercise stress test in an angiographically documented high prevalence population.
Nowak J; Hagerman I; Ylén M; Nyquist O; Sylvén C
Clin Cardiol; 1993 Sep; 16(9):671-82. PubMed ID: 8242912
[TBL] [Abstract][Full Text] [Related]
6. Predicting severe angiographic coronary artery disease using computerization of clinical and exercise test data.
Do D; Marcus R; Froelicher V; Janosi A; West J; Atwood JE; Myers J; Chilton R; Froning J
Chest; 1998 Nov; 114(5):1437-45. PubMed ID: 9824025
[TBL] [Abstract][Full Text] [Related]
7. Accurate detection of coronary artery disease by integrated analysis of the ST-segment depression/heart rate patterns during the exercise and recovery phases of the exercise electrocardiography test.
Lehtinen R; Sievänen H; Viik J; Turjanmaa V; Niemelä K; Malmivuo J
Am J Cardiol; 1996 Nov; 78(9):1002-6. PubMed ID: 8916478
[TBL] [Abstract][Full Text] [Related]
8. The effect of resting ST segment depression on the diagnostic characteristics of the exercise treadmill test.
Fearon WF; Lee DP; Froelicher VF
J Am Coll Cardiol; 2000 Apr; 35(5):1206-11. PubMed ID: 10758962
[TBL] [Abstract][Full Text] [Related]
9. Quantitative evaluation of exercise-induced ST-segment depression for estimation of degree of coronary artery disease.
Berényi I; Hajduczki IS; Böszörményi E
Eur Heart J; 1984 Apr; 5(4):289-94. PubMed ID: 6734638
[TBL] [Abstract][Full Text] [Related]
10. Improved accuracy of the exercise electrocardiogram in detection of coronary artery and three-vessel coronary disease.
Sato I; Keta K; Aihara N; Ohe T; Shimomura K; Hasegawa Y
Chest; 1988 Oct; 94(4):737-44. PubMed ID: 3168570
[TBL] [Abstract][Full Text] [Related]
11. [Exercise haemodynamics and ECG in the evaluation of the severity of coronary heart disease (author's transl)].
Slany J
Wien Klin Wochenschr Suppl; 1978; 87():1-30. PubMed ID: 347722
[TBL] [Abstract][Full Text] [Related]
12. The effect of lead selection on traditional and heart rate-adjusted ST segment analysis in the detection of coronary artery disease during exercise testing.
Viik J; Lehtinen R; Turjanmaa V; Niemelä K; Malmivuo J
Am Heart J; 1997 Sep; 134(3):488-94. PubMed ID: 9327707
[TBL] [Abstract][Full Text] [Related]
13. Gender-specific criteria and performance of the exercise electrocardiogram.
Okin PM; Kligfield P
Circulation; 1995 Sep; 92(5):1209-16. PubMed ID: 7648667
[TBL] [Abstract][Full Text] [Related]
14. Comparison of computer ST criteria for diagnosis of severe coronary artery disease.
Ribisl PM; Liu J; Mousa I; Herbert WG; Miranda CP; Froning JN; Froelicher VF
Am J Cardiol; 1993 Mar; 71(7):546-51. PubMed ID: 8094938
[TBL] [Abstract][Full Text] [Related]
15. Diagnostic value of computerized exercise testing in men without previous myocardial infarction. A multivariate, compartmental and probabilistic approach.
Detry JM; Robert A; Luwaert RJ; Rousseau MF; Brasseur LA; Melin JA; Brohet CR
Eur Heart J; 1985 Mar; 6(3):227-38. PubMed ID: 4029179
[TBL] [Abstract][Full Text] [Related]
16. Acoustical detection of coronary occlusions using neural networks.
Akay M; Welkowitz W
J Biomed Eng; 1993 Nov; 15(6):469-73. PubMed ID: 8277750
[TBL] [Abstract][Full Text] [Related]
17. Visual versus computerized analysis of upsloping ST segment depression in the exercise electrocardiogram.
Walamies MA; Kööbi T; Hämäläinen LI; Ahonen EA
Cardiology; 1999; 92(4):264-8. PubMed ID: 10844387
[TBL] [Abstract][Full Text] [Related]
18. Accuracy of exercise electrocardiography in detecting physiologically significant coronary arterial lesions.
Wilson RF; Marcus ML; Christensen BV; Talman C; White CW
Circulation; 1991 Feb; 83(2):412-21. PubMed ID: 1991365
[TBL] [Abstract][Full Text] [Related]
19. [Accuracy of exercise tests in the recognition of coronary-artery stenosis. Comparison between post-exercise ECG and coronary arteriogram (author's transl)].
Kaltenbach M; Martin KL; Hopf R
Dtsch Med Wochenschr; 1976 Dec; 101(52):1907-11. PubMed ID: 1001216
[TBL] [Abstract][Full Text] [Related]
20. Artificial neural network models for prediction of acute coronary syndromes using clinical data from the time of presentation.
Harrison RF; Kennedy RL
Ann Emerg Med; 2005 Nov; 46(5):431-9. PubMed ID: 16271675
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]