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ABCD rule and pre-trained CNNs for melanoma diagnosis., , , , , , и . Multim. Tools Appl., 78 (6): 6869-6888 (2019)Automatic Detection of Glaucoma Using Disc Optic Segmentation and Feature Extraction., , , , , и . CLEI, стр. 1-7. IEEE, (2015)Automatic Segmentation of Lung Nodules in CT Images Using Deep Learning., , , , и . HealthCom, стр. 1-6. IEEE, (2020)An hybrid feature space from texture information and transfer learning for glaucoma classification., , , , , , и . J. Vis. Commun. Image Represent., (2019)Leukemia diagnosis in blood slides using transfer learning in CNNs and SVM for classification., , , , и . Eng. Appl. Artif. Intell., (2018)Diagnosis of Leukaemia in Blood Slides Based on a Fine-Tuned and Highly Generalisable Deep Learning Model., , , , , , и . Sensors, 21 (9): 2989 (2021)Malignant breast lesions detection in histopathological images based on the combination of bioinspired texture descriptors and deep features., , , , и . Comput. methods Biomech. Biomed. Eng. Imaging Vis., 11 (5): 1889-1896 (сентября 2023)Evaluation of the use of computational intelligence techniques in medical claim processes of a health insurance company., , , , , и . CBMS, стр. 23-28. IEEE Computer Society, (2013)Texture Maps as Input in 3D CNNs Applied to Classify Nodules in CT Images., , , , и . HealthCom, стр. 1-6. IEEE, (2020)Prediction of COVID-19 using Time-Sliding Window: The case of Piauí State - Brazil., , , , , , , , , и . HealthCom, стр. 1-6. IEEE, (2020)