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Volumn 150, Issue 1, 2015, Pages 247-249

Quantifying regional left ventricular contractile function: Leave it to the machines?

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY; CARDIOVASCULAR MAGNETIC RESONANCE; CLINICAL DECISION MAKING; CLINICAL PRACTICE; CORONARY ARTERY DISEASE; DISEASE SEVERITY; ECHOCARDIOGRAPHY; ELECTROCARDIOGRAPHY; HEART LEFT VENTRICLE CONTRACTION; HUMAN; LARGE CELL LYMPHOMA; LEARNING ALGORITHM; MACHINE LEARNING; NOTE; PRIORITY JOURNAL; PROGNOSIS; SENSITIVITY AND SPECIFICITY; SINGLE PHOTON EMISSION COMPUTER TOMOGRAPHY; FEMALE; HEART LEFT VENTRICLE FUNCTION; HEART MUSCLE ISCHEMIA; MALE; PATHOPHYSIOLOGY;

EID: 84941800828     PISSN: 00225223     EISSN: 1097685X     Source Type: Journal    
DOI: 10.1016/j.jtcvs.2015.04.034     Document Type: Editorial
Times cited : (2)

References (7)
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  • 2
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  • 4
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    • Machine learning for detection and diagnosis of disease
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    • M.A. Shipp, K.N. Ross, P. Tamayo, A.P. Weng, J.L. Kutok, R.C. Aguiar, and et al. Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning Nat Med 8 2002 68 74
    • (2002) Nat Med , vol.8 , pp. 68-74
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.