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{"references": ["1.\tAntony, L., Azam, S., Ignatious, E., Quadir, R., Beeravolu, A. R., Jonkman, M., & De Boer, F. (2021). A comprehensive unsupervised framework for chronic kidney disease prediction. IEEE Access, 9, 126481-126501.", "2.\tAkshaya, M., Nithushaa, R., Raja, N. S. M., & Padmapriya, S. (2020, July). Kidney Stone Detection Using Neural Networks. In 2020 International Conference on System, Computation, Automation and Networking (ICSCAN) (pp. 1-4). IEEE.", "3.\tRavindra, B. V., Sriraam, N., & Geetha, M. J. I. J. E. T. (2018). Classification of non-chronic and chronic kidney disease using SVM neural networks. Int. J. Eng. Technol, 7(1), 191-194.", "4.\tYashfi, S. Y., Islam, M. A., Sakib, N., Islam, T., Shahbaaz, M., & Pantho, S. S. (2020, July). Risk prediction of chronic kidney disease using machine learning algorithms. In 2020 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT) (pp. 1-5). IEEE.", "5.\tJain, D., & Singh, V. (2018). Feature selection and classification systems for chronic disease prediction: A review. Egyptian Informatics Journal, 19(3), 179-189.", "6.\tAkkasaligar, P. T., & Biradar, S. (2014). Classification of medical ultrasound images of kidney. Int J Comput Appl, 3, 24-28."]}
Kidney stones have increased in prevalence in recent years, and early detection is essential since failure to do so may lead to problems and the need for surgical removal of the stone. Because image processing has a bias towards producing exact findings and is an automatically scalable approach of stone detection, it opens the way for accurate stone detection. Due to their size and location, kidney stones might be difficult to see with ultrasonography.Kidney stones have increased in prevalence in recent years, and early detection is essential since failure to do so may lead to problems and the need for surgical removal of the stone. Because image processing has a bias towards producing exact findings and is an automatically scalable approach of stone detection, it opens the way for accurate stone detection. Due to their size and location, kidney stones might be difficult to see with ultrasonography.
Kidney stones, MLP-BP ANN, CNN (Convolutional Neural Network)
Kidney stones, MLP-BP ANN, CNN (Convolutional Neural Network)
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