Deep Learning–based Prediction of Percutaneous Recanalization in Chronic Total Occlusion Using Coronary CT Angiography
Zhen Zhou(Capital Medical University), Lei Xu(Fudan University), Koen Nieman(University of British Columbia), Heye Zhang(Sun Yat-sen University), Nan Zhang(Second Hospital of Tianjin Medical University), Guang Yang(Imperial College London), Weiwei Zhang(Sun Yat-sen University), Rui Wang(Xuzhou Medical College), Hui Wang(Qingdao University), Shanshan Zhou(Guangzhou University of Chinese Medicine), Xu Dai(Beijing Anzhen Hospital), Yifeng Gao(German Cancer Research Center), Xiaomeng Huang(Beijing Anzhen Hospital), Zhifan Gao(Sun Yat-sen University)
Cited by 21
Related Papers
SCCT 2021 Expert Consensus Document on Coronary Computed Tomographic Angiography: A Report of the Society of Cardiovascular Computed Tomography
|Journal of cardiovascular computed tomography|2020|368
1-Year Impact on Medical Practice and Clinical Outcomes of FFRCT
|JACC. Cardiovascular imaging|2019|309
Real-world clinical utility and impact on clinical decision-making of coronary computed tomography angiography-derived fractional flow reserve: lessons from the ADVANCE Registry
|European Heart Journal|2018|305
Cilostazol as an alternative to aspirin after ischaemic stroke: a randomised, double-blind, pilot study
|The Lancet Neurology|2008|262
Heat transfer characteristics of refrigerant-based nanofluid flow boiling inside a horizontal smooth tube
|International Journal of Refrigeration|2009|257