Acute myocardial infarction detected in the 12-lead ECG by artificial neural networks

Circulation

Volumn 96, Issue 6, 1997, Pages 1798-1802

  Hedén, Bo ^b   Öhlin, Hans ^b   Rittner, Ralf ^b   Edenbrandt, Lars ^a  

^a LUND UNIVERSITY HOSPITAL   (Sweden)

^b NONE

Author keywords

Artificial intelligence; Diagnosis; Electrocardiography; Myocardial infarction

Indexed keywords

ACUTE HEART INFARCTION; ARTICLE; ARTIFICIAL NEURAL NETWORK; AUTOMATION; CONTROLLED STUDY; DIAGNOSTIC VALUE; ELECTROCARDIOGRAM; HUMAN; MAJOR CLINICAL STUDY; PRIORITY JOURNAL;

EID: 0030823688     PISSN: 00097322     EISSN: None     Source Type: Journal    
DOI: 10.1161/01.CIR.96.6.1798     Document Type: Article

References (20)

1. Timmis AD. Early diagnosis of acute myocardial infarction. BMJ. 1990;301:941-942.
2. Timmis AD. Will serum enzymes and other proteins find a clinical application in the early diagnosis of myocardial infarction? Br Heart J. 1994;71:309-310.
3. Lee HS, Cross SL, Garthwaite P, Dickie A, Ross I, Walton S, Jennings K. Comparison of the value of novel rapid measurement of myoglobin, creatine kinase, and creatine kinase-MB with the electrocardiogram for the diagnosis of acute myocardial infarction. Br Heart J. 1994;71:311-315.
4. Mair J, Smidt J, Lechleitner P, Dienstl F, Puschendorf B. A decision tree for the early diagnosis of acute myocardial infarction in nontraumatic chest pain patients at hospital admission. Chest. 1995;108:1502-1509.
5. McCarthy BD, Beshansky JR, D'Agostino RB, Selker HP. Missed diagnoses of acute myocardial infarction in the emergency department: results from a multicenter study. Ann Emerg Med. 1993;22:579-582.
6. Puleo RP, Meyer D, Wathen C, Tawa CB, Wheeler S, Hamburg RJ, Ali N, Obermueller SD, Triana JF, Zimmerman JL, Ferryman B, Roberts R. Use of a rapid assay of subforms of creatine kinase MB to diagnose or rule out acute myocardial infarction. N Engl J Med. 1994;331:561-566.
7. Roberts R, Kleiman NS. Earlier diagnosis and treatment of acute myocardial infarction necessitates the need for a 'new diagnostic mind set.' Circulation. 1994;89:872-881.
8. Cross SS, Harrison RF, Kennedy RL. Introduction to neural networks. Lancet. 1995;346:1075-1079.
9. Baxt WG. Application of artificial neural networks to clinical medicine. Lancet. 1995;346:1135-1138.
10. Hedén B, Edenbrandt L, Haisty WK Jr, Pahlm O. Artificial neural networks for the electrocardiographic diagnosis of healed myocardial infarction. Am J Cardiol. 1994;74:5-8.
11. Hedén B, Ohlsson M, Edenbrandt L, Rittner R, Pahlm O, Peterson C. Artificial neural networks for recognition of electrocardiographic lead reversal. Am J Cardiol. 1995;75:929-933.
12. Hedén B, Ohlsson M, Rittner R, Pahlm O, Haisty WK Jr, Peterson C, Edenbrandt L. Agreement between artificial neural networks and human expert for the electrocardiographic diagnosis of healed myocardial infarction. J Am Coll Cardiol. 1996;28:1012-1016.
13. Bortolan G, Willems JL. Diagnostic ECG classification based on neural networks. J Electrocardiol. 1993;26(suppl):75-79.
14. Clayton RH, Murray A, Campbell RWF. Recognition of ventricular fibrillation using neural networks. Med Biol Eng Comput. 1994;32: 217-220.
15. Baxt WG, Skora J. Prospective validation of artificial neural network trained to identify acute myocardial infarction. Lancet. 1996;347:12-15.
16. Rumelhart DE, McClelland JL, eds. Parallel Distributed Processing, Volumes 1 and 2. Cambridge, Mass: MIT Press; 1986.
17. Rögnvaldsson T. On Langevin updating in multilayer perceptrons. Neural Comput. 1994;6:916-926.
18. Peterson C, Rögnvaldsson T, Lönnblad L. JETNET 3.0: a versatile artificial neural network package. Comput Phys Commun. 1994;81: 185-220.
19. Macfarlane PW, Lawrie TDV. Comprehensive Electrocardiology. Oxford, UK: Pergamon Press Inc; 1989;3:1554-1561.
20. Blakeley DD, Oddone EZ, Hasselblad V, Simel DL, Matchar DB. Noninvasive carotid artery testing: a meta-analytic review. Ann Intern Med. 1995;122:360-367.