Atıf İçin Kopyala
Alis D. C., Guler A., Yergin M., Asmakutlu O.
DIAGNOSTIC AND INTERVENTIONAL IMAGING, cilt.101, sa.3, ss.137-146, 2020 (SCI-Expanded)
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Yayın Türü:
Makale / Tam Makale
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Cilt numarası:
101
Sayı:
3
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Basım Tarihi:
2020
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Doi Numarası:
10.1016/j.diii.2019.10.005
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Dergi Adı:
DIAGNOSTIC AND INTERVENTIONAL IMAGING
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Derginin Tarandığı İndeksler:
Science Citation Index Expanded (SCI-EXPANDED), Scopus, EMBASE, MEDLINE
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Sayfa Sayıları:
ss.137-146
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Anahtar Kelimeler:
Artificial intelligence, Cardiomyopathy, Hypertrophic, Machine learning, Tachycardia, Ventricular, Texture analysis, MYOCARDIAL SCAR, DIAGNOSIS, QUANTIFICATION, SEGMENTATION, ASSOCIATION, TACHYCARDIA, VALIDATION, CARDIOLOGY, CANCER, MAZDA
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Acıbadem Mehmet Ali Aydınlar Üniversitesi Adresli:
Evet
Özet
Objective: To assess the diagnostic value of machine learning-based texture feature analysis of late gadolinium enhancement images on cardiac magnetic resonance imaging (MRI) for assessing the presence of ventricular tachyarrhythmia (VT) in patients with hypertrophic cardiomyopathy.