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Accurate Detection of Septal Defects With Fetal Ultrasonography Images Using Deep Learning-Based Multiclass Instance Segmentation., , , , , , , and . IEEE Access, (2020)Automatic echocardiographic anomalies interpretation using a stacked residual-dense network model., , , , , , , , , and . BMC Bioinform., 24 (1): 365 (December 2023)Automated Precancerous Lesion Screening Using an Instance Segmentation Technique for Improving Accuracy., , , , , , , , , and . Sensors, 22 (15): 5489 (2022)Accurate Fetal QRS-Complex Classification from Abdominal Electrocardiogram Using Deep Learning., , , , , , , and . Int. J. Comput. Intell. Syst., 16 (1): 158 (December 2023)An improved semantic segmentation with region proposal network for cardiac defect interpretation., , , , , , and . Neural Comput. Appl., 34 (16): 13937-13950 (2022)CervicoXNet: an automated cervicogram interpretation network., , , , , , , , , and . Medical Biol. Eng. Comput., 61 (9): 2405-2416 (September 2023)Improved delineation model of a standard 12-lead electrocardiogram based on a deep learning algorithm., , , , , , , and . BMC Medical Informatics Decis. Mak., 23 (1): 139 (December 2023)Deep Learning-Based Computer-Aided Fetal Echocardiography: Application to Heart Standard View Segmentation for Congenital Heart Defects Detection., , , , , , , and . Sensors, 21 (23): 8007 (2021)Beat-to-Beat Electrocardiogram Waveform Classification Based on a Stacked Convolutional and Bidirectional Long Short-Term Memory., , , , , , and . IEEE Access, (2021)Deep learning-based electrocardiogram rhythm and beat features for heart abnormality classification., , , , , , , and . PeerJ Comput. Sci., (2022)