[1] Souza-Pereira, L., Pombo, N., Ouhbi, S., Felizardo, V. and Garcia, N., 2020. "Clinical decision support systems for chronic diseases: A systematic literature review", Computer Methods and Programs in Biomedicine, Vol. 195, pp. 105565.
[2] Alkenani, A. H., Li, Y., Xu, Y. & Zhang, Q., 2021. "Predicting Alzheimer’s disease from spoken and written language using fusion-based stacked generalization", Journal of Biomedical Informatics, Vol. 118, pp. 103803.
[3] Yuan, X., Chen, S., Yuwen, L., An, S., Mei, S. & Chen, T., 2020. "An improved SEIR model for reconstructing the dynamic transmission of COVID-19", In Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 2320 – 2327.
[4] Guo, Y. et al., 2021. "A review of wearable and unobtrusive sensing technologies for chronic disease management", Computers in Biology and Medicine, Vol. 129, pp. 104163.
[5] Wang, Haidong, et al., 2016. "Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: a systematic analysis for the Global Burden of Disease Study 2015", The lancet 388, Vol. 10053, pp. 1459-1544.
[6] Beyer, K.M., Namin, S., 2023. "Chronic environmental diseases: burdens, causes, and response", In Biological and environmental hazards, risks, and disasters, Elsevier, pp. 223-249.
[8] نورالدّینی، صدرالدّین.، 1400. "اثر اقتصادی بیمار یها ی مزمن بر هزینه و درآمد خانوار ایرانی"، نشریه علمی (فصلنامه)، پژوهشها و سیاستهای اقتصادی شماره 9 ، صفحه 207 – 241.
[9] Delpino, F.M., Costa, Â.K., Farias, S.R., Chiavegatto Filho, A.D.P., Arcêncio, R.A. and Nunes, B.P., 2022. "Machine learning for predicting chronic diseases: a systematic review", Public Health, Vol. 205, pp.14-25.
[10] Maniruzzaman, M., Rahman, M.J., Ahammed, B. and Abedin, M.M., 2020. "Classification and prediction of diabetes disease using machine learning paradigm", Health information science and systems, Vol. 8, pp. 1-14.
[11] Huang, J., Huth, C., Covic, M., Troll, M., Adam, J., Zukunft, S., Prehn, C., Wang, L., Nano, J., Scheerer, M.F. and Neschen, S., 2020. "Machine learning approaches reveal metabolic signatures of incident chronic kidney disease in individuals with prediabetes and type 2 diabetes", Diabetes, Vol. 69(12), pp.2756-2765.
[12] Zhang, L., Yuan, M., An, Z., Zhao, X., Wu, H., Li, H., Wang, Y., Sun, B., Li, H., Ding, S. and Zeng, X., 2020. "Prediction of hypertension, hyperglycemia and dyslipidemia from retinal fundus photographs via deep learning: A cross-sectional study of chronic diseases in central China", PloS one, Vol. 15(5), p.e0233166.
[13] Al-Azzam, N. and Shatnawi, I., 2021. "Comparing supervised and semi-supervised machine learning models on diagnosing breast cancer", Annals of Medicine and Surgery, V0l. 62, pp.53-64.
[14] Xie, Y., Meng, W.Y., Li, R.Z., Wang, Y.W., Qian, X., Chan, C., Yu, Z.F., Fan, X.X., Pan, H.D., Xie, C. and Wu, Q.B., 2021. "Early lung cancer diagnostic biomarker discovery by machine learning methods", Translational oncology, V0l. 14(1), pp. 100907.
[15] Mezzatesta, S., Torino, C., De Meo, P., Fiumara, G. and Vilasi, A., 2019. "A machine learning-based approach for predicting the outbreak of cardiovascular diseases in patients on dialysis", Computer methods and programs in biomedicine, Vol. 177, pp. 9-15.
[16] Yuan, X., Chen, S., Sun, C. and Yuwen, L., 2022. "A novel early diagnostic framework for chronic diseases with class imbalance", Scientific Reports, Vol. 12(1), pp. 8614.
[17] Tanveer, M., Rajani, T., Rastogi, R., Shao, Y.H. and Ganaie, M.A., 2022. Comprehensive review on twin support vector machines. Annals of Operations Research, pp.1-46.
[18] ناجی عظیمی. زهرا، تابستان 95، آشنایی با برنامهریزی خطی فازی، ویراستة وحیدیان کامیاد، علی، ویرایش اوّل، مشهد، انتشارات دانشگاه فردوسی مشهد.
[19] سبزهکار، مصطفی، آذر 88، بررسی تأثیر توجه مضاعف به نمونههای یادگیری با استفاده از قیود بهینهسازی طبقهبندهای ماشین بردار پشتیبان، پایاننامة کارشناسی ارشد، گروه مهندسی کامپیوتر، دانشکده مهندسی، دانشگاه فردوسی مشهد، صفحات 82-90.
[20] Jayadeva, Khemchandani, R. and Chandra, S., 2018. "Twin support vector machines: models, extensions and applications", Springer Publishing Company, Incorporated.
[21] Nasiri, J.A. and Mir, A.M., 2020. "An enhanced KNN-based twin support vector machine with stable learning rules", Neural computing and applications, Vol. 32(16), pp.12949-12969.
[22] Mozafari, K., Nasiri, J.A., Charkari, N.M. and Jalili, S., 2011, December. Action recognition by local space-time features and least square twin SVM (LS-TSVM). In 2011 first international conference on informatics and computational intelligence (pp. 287-292). IEEE.
[23] Raschka, S. and Mirjalili, V. 2017, Python machine learning second edition. Birmingham, England: Packt Publishing.
[24] Yuan, X., Chen, S., Sun, C. and Yuwen, L., 2022, "A novel early diagnostic framework for chronic diseases with class imbalance", Scientific Reports, Vol. 12(1), pp. 8614.