Diagnosis of Acute Coronary Syndrome with a Support Vector Machine

Journal of Medical Systems

Volumn 40, Issue 4, 2016, Pages 1-8

  Berikol, Göksu Bozdereli ^a,b,c   Yildiz, Oktay ^a,b,c   Özcan, İ Türkay ^a,b,c  

^a Karaman State Hospital   (Turkey)

^b GAZI UNIVERSITY   (Turkey)

^c MERSIN UNIVERSITY   (Turkey)

Author keywords

Acute coronary syndrome; Artificial intelligence; Machine learning; Support vector machine

Indexed keywords

CREATINE KINASE MB; TROPONIN I;

ACUTE CORONARY SYNDROME; ADULT; AGED; ARTICLE; ARTIFICIAL NEURAL NETWORK; BAYESIAN LEARNING; CLINICAL DECISION MAKING; DIAGNOSTIC ACCURACY; DIAGNOSTIC TEST ACCURACY STUDY; ELECTROCARDIOGRAPHY; EMERGENCY WARD; FEMALE; HUMAN; LABORATORY TEST; LOGISTIC REGRESSION ANALYSIS; MACHINE LEARNING; MAJOR CLINICAL STUDY; MALE; SUPPORT VECTOR MACHINE; THORAX PAIN; AGE; BAYES THEOREM; BLOOD; CLINICAL DECISION SUPPORT SYSTEM; MIDDLE AGED; REPRODUCIBILITY; RISK FACTOR; SEX DIFFERENCE; STATISTICAL MODEL; VERY ELDERLY;

ACUTE CORONARY SYNDROME; ADULT; AGE FACTORS; AGED; AGED, 80 AND OVER; BAYES THEOREM; CHEST PAIN; CREATINE KINASE, MB FORM; DECISION SUPPORT SYSTEMS, CLINICAL; ELECTROCARDIOGRAPHY; FEMALE; HUMANS; LOGISTIC MODELS; MALE; MIDDLE AGED; NEURAL NETWORKS (COMPUTER); REPRODUCIBILITY OF RESULTS; RISK FACTORS; SEX FACTORS; SUPPORT VECTOR MACHINE; TROPONIN I;

EID: 84956503197     PISSN: 01485598     EISSN: 1573689X     Source Type: Journal    
DOI: 10.1007/s10916-016-0432-6     Document Type: Article

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