RF-CNN-F: random forest with convolutional neural network features for coronary artery disease diagnosis based on cardiac magnetic resonance

RF-CNN-F: random forest with convolutional neural network features for coronary artery disease diagnosis based on cardiac magnetic resonance

Coronary artery disease (CAD) is a prevalent disease with high morbidity and mortality rates. Invasive coronary angiography is the reference standard for diagnosing CAD but is costly and associated with risks. Noninvasive imaging like cardiac magnetic resonance (CMR) facilitates CAD assessment and c...

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Bibliographic Details
Main Authors: Acharya, U.R (Author), Alizadehsani, R. (Author), Hussain, S. (Author), Islam, S.M.S (Author), Izadi, N.H (Author), Joloudari, J.H (Author), Khodatars, M. (Author), Khosravi, A. (Author), Khozeimeh, F. (Author), Nahavandi, S. (Author), Sadeghi, D. (Author), Sani, Z.A (Author), Sharifrazi, D. (Author), Shoeibi, A. (Author), Tan, R.-S (Author), Tartibi, M. (Author)
Format: Article
Language:English
Published: Nature Research 2022
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