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Agarwal, D., Singh, P., & El Sayed, M. (2023). The Karush–Kuhn–Tucker (KKT) optimality conditions for fuzzy-valued fractional optimization problems. Mathematics and Computers in Simulation, 205, 861-877.
Battineni, G., Chintalapudi, N., & Amenta, F. (2019). Machine learning in medicine: Performance calculation of dementia prediction by support vector machines (SVM). Informatics in Medicine Unlocked, 16, 100200.
Bhat, A. (2021). Kaggle. Retrieved from https://www.kaggle.com/datasets/mysarahmadbhat/lung-cancer
Davies, M., Takahiro, S., Haitham, A., Liping, H., Triantafillos, L., Yang, R., & Field, J. (2023). Plasma protein biomarkers for early prediction of lung cancer. eBioMedicine, Volume 93, 104686.
Ibragimov, S. (2023). Raqamli dasturiy mahsulot yaratish asosida onkoepidemiologik holatni kompleks baholash [Comprehensive assessment of the oncoepidemiological situation based on the creation of a digital software product]. Tashkent.
IQAIR. (2024). Air quality in Tashkent. Air quality index (AQI) and PM2.5 air pollution in Tashkent. (Keystone, IQAIR). Retrieved from IQAIR: https://www.iqair.com/ru/uzbekistan/toshkent-shahri/tashkent
Keerthana, D., Venugopal, V., Nath, M., & Mishra, M. (2023). Hybrid convolutional neural networks with SVM classifier for classification of skin cancer. Biomedical Engineering Advances, 5, 100069.
Khudayberdiev, M., Ibragimov, S., Alimkulov, N., & Djanklich, S. (2023). Solving tasks of oncoepidemiology prediction using least squares and SVR algorithms. В T. &. Group (Ed.), Artificial Intelligence, Blockchain, Computing and Security Volume 2 (pр. 595-602). London: CRC Press.
Kumar, K., Srikanth, V., Prasad, G., Hazela, B., & Tamrakar, A. (2023). Fault detection on the 3-D printed objective surface by using the SVM algorithm. Materials Today: Proceedings.
Lan, Y., Zhang, Y., & Lin, W. (2023). Diagnosis algorithms for indirect bridge health monitoring via an optimized AdaBoost-linear SVM. Engineering Structures, 275(Part A), 115239.
Liu, J., & Liu, Y. (2014). Non-integer norm regularization SVM via Legendre–Fenchel duality. Neurocomputing, 144, 537-545.
Nasser, I.M.; Abu-Naser, S.S. (2019). Lung Cancer Detection Using Artificial Neural Network. International Journal of Engineering and Information Systems, 3(3), 17-23.
Qiang, Y., Guo, Y., Li, X., Wang, Q., Chen, H., & Cuic, D. (2007). The Diagnostic Rules of Peripheral Lung Cancer Preliminary Study Based on Data Mining Technique. Journal of Nanjing Medical University, 190-195.
Rikta, S., Uddin, K., Biswas, N., Mostafiz, R., Sharmin, F., & Dey, S. (2023). XML-GBM lung: An explainable machine learning-based application for the diagnosis of lung cancer. Journal of Pathology Informatics, 14, 100307.
Tillyashaykhova, M., Ibragimova, S., & Dzhanklich, S. (2023). Sostoyaniye onkologicheskoy pomoshchi naseleniyu Respubliki Uzbekistan v 2022 godu [The state of cancer care for the population of the Republic of Uzbekistan in 2022]. Tashkent: Khalk Publ.
Vankdothu, R., & Hameed, M. (2022). Brain tumor segmentation of MR images using SVM and fuzzy classifier in machine learning. Measurement: Sensors, 24, 100440.
Wu, Y., & Li, S. (2022). Damage degree evaluation of masonry using optimized SVM-based acoustic emission monitoring and rate process theory. Measurement, 190, 110729.
Yang, M., Lim, M., Qu, Y., Li, X., & Ni, D. (2023). Deep neural networks with L1 and L2 regularization for high dimensional corporate credit risk prediction. Expert Systems with Applications, 213(Part A).