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Use of Nonlinear Features for Automated Characterization of Suspicious Ovarian Tumors Using Ultrasound Images in Fuzzy Forest Framework.

, , , , , , , , , , , and . Int. J. Fuzzy Syst., 20 (4): 1385-1402 (2018)

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Automated detection and localization of myocardial infarction using electrocardiogram: a comparative study of different leads., , , , , , , , , and 2 other author(s). Knowl. Based Syst., (2016)Use of Nonlinear Features for Automated Characterization of Suspicious Ovarian Tumors Using Ultrasound Images in Fuzzy Forest Framework., , , , , , , , , and 2 other author(s). Int. J. Fuzzy Syst., 20 (4): 1385-1402 (2018)Application of entropies for automated diagnosis of epilepsy using EEG signals: A review., , , , and . Knowl. Based Syst., (2015)Automated characterization and classification of coronary artery disease and myocardial infarction by decomposition of ECG signals: A comparative study., , , , , , , , , and 1 other author(s). Inf. Sci., (2017)Application of higher-order spectra for the characterization of Coronary artery disease using electrocardiogram signals., , , , , , , , , and 2 other author(s). Biomed. Signal Process. Control., (2017)An integrated index for identification of fatty liver disease using radon transform and discrete cosine transform features in ultrasound images., , , , , , , , , and 1 other author(s). Inf. Fusion, (2016)Automated characterization of arrhythmias using nonlinear features from tachycardia ECG beats., , , , , , and . SMC, page 533-538. IEEE, (2016)Automated classification of attention deficit hyperactivity disorder and conduct disorder using entropy features with ECG signals., , , , , , , , and . Comput. Biol. Medicine, (2022)Computer-aided diagnosis of glaucoma using fundus images: A review., , , , , , , and . Comput. Methods Programs Biomed., (2018)Automated Prediction of Sudden Cardiac Death Risk Using Kolmogorov Complexity and Recurrence Quantification Analysis Features Extracted from HRV Signals., , , , , and . SMC, page 1110-1115. IEEE, (2015)