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Automated detection and forecasting of COVID-19 using deep learning techniques: A review., , , , , , , , , and 5 other author(s). Neurocomputing, (2024)A data mining approach for diagnosis of coronary artery disease., , , , , , , and . Comput. Methods Programs Biomed., 111 (1): 52-61 (2013)Exerting Cost-Sensitive and Feature Creation Algorithms for Coronary Artery Disease Diagnosis., , , , , and . Int. J. Knowl. Discov. Bioinform., 3 (1): 59-79 (2012)Characterisation of the effects of age and body mass index on the ultrasound carotid artery wall using RF time series., , and . Comput. methods Biomech. Biomed. Eng. Imaging Vis., 8 (2): 134-142 (2020)Objective Evaluation of Deep Uncertainty Predictions for COVID-19 Detection., , , , , , and . CoRR, (2020)Uncertainty-Aware Semi-Supervised Method Using Large Unlabeled and Limited Labeled COVID-19 Data., , , , , , , , , and 4 other author(s). ACM Trans. Multim. Comput. Commun. Appl., 17 (3s): 104:1-104:24 (2021)A new technique for the measurement and assessment of carotid artery wall vibrations using ultrasound RF echoes., , and . Turkish J. Electr. Eng. Comput. Sci., 27 (6): 4340-4353 (2019)Diagnosis of Coronary Artery Disease Using Cost-Sensitive Algorithms., , , , and . ICDM Workshops, page 9-16. IEEE Computer Society, (2012)Echocardiography noise reduction using sparse representation., , , , and . Comput. Electr. Eng., (2016)