Levenberg-Marquardt backpropagation neural network procedures for the consumption of hard water-based kidney function

[1] Razzaque S., Aidrus F., Kumar A., Kumar A., Ghauri I., Ullah S., Hypertension in people consuming hard water in Haji Samoa Goth Keti-Bundar Sindh, Annals of Abbasi Shaheed Hospital and Karachi Medical and Dental College, 20(1), 17-22, 2015. Search in Google Scholar

[2] Abraham G., Varughese S., Thandavan T., Iyengar A., Fernando E., Naqvi S.A.J., Sheriff R., Rashid H., Gopalakrishnan N., Kafle R.K., Chronic kidney disease hotspots in developing countries in South Asia, Clinical Kidney Journal, 9(1), 135-141, 2016. Search in Google Scholar

[3] Noormaningrum B.R., Nurhantari Y., Suhartini S., Ratnaningsih T., Dedy M.A.E., Alcohol dehydrogenase 1C (ADH1C) polymorphism is significantly associated with kidney function status in Nusa Tenggara Timur ethnicity: A cross-sectional study, Journal of Community Empowerment for Health, 4(3), 162-168, 2021. Search in Google Scholar

[4] Landrigan P.J., Kimmel C.A., Correa A., Eskenazi B., Children’s health and the environment: public health issues and challenges for risk assessment, Environmental Health Perspectives, 112(2), 257-265, 2004. Search in Google Scholar

[5] Ndii M.Z., Allingham D., Hickson R.I., Glass K., The effect of Wolbachia on dengue dynamics in the presence of two serotypes of dengue: symmetric and asymmetric epidemiological characteristics, Epidemiology and Infection, 144(13), 2874-2882, 2016. Search in Google Scholar

[6] Paul S., Mahata A., Mukherjee S., Mali P.C., Roy B., Dynamical behavior of a fractional order SIR model with stability analysis, Results in Control and Optimization, 10(100212), 1-13, 2023. Search in Google Scholar

[7] Andraud M., Hens N., Marais C., Beutels P., Dynamic epidemiological models for dengue transmission: a systematic review of structural approaches, Plos One, 7(11), e49085, 2012. Search in Google Scholar

[8] Ruttanaprommarin N., Sabir Z., Núñez R.A.S., Salahshour S., Guirao J.L.G., Weera W., Botmart T., Klamnoi A., Artificial neural network procedures for the waterborne spread and control of diseases, AIMS Mathematics, 8(1), 2435-2452, 2023. Search in Google Scholar

[9] Chitnis N., Hyman J.M., Cushing J.M., Determining important parameters in the spread of malaria through the sensitivity analysis of a mathematical model, Bulletin of Mathematical Biology, 70(5), 1272-1296, 2008. Search in Google Scholar

[10] Ndii M.Z., Amarti Z., Wiraningsih E.D., Supriatna A.K., Rabies epidemic model with uncertainty in parameters: crisp and fuzzy approaches, IOP conference series: Materials Science and Engineering, 332(012031), 1-9, 2018. Search in Google Scholar

[11] Ndii M.Z., Supriatna A.K., Stochastic mathematical models in epidemiology, Information, 20, 6185-6196, 2017. Search in Google Scholar

[12] Hao W., Rovin B.H., Friedman A., Mathematical model of renal interstitial fibrosis, Proceedings of the National Academy of Sciences, 111(39), 14193-14198, 2014. Search in Google Scholar

[13] Clemmer J.S., Pruett W.A., Coleman T.G., Hall J.E., Hester R.L., Mechanisms of blood pressure salt sensitivity: new insights from mathematical modeling, American Journal of Physiology-Regulatory, Integrative and Comparative Physiology, 312(4), R451-R466, 2017. Search in Google Scholar

[14] Lin J., Knight E.L., Hogan M.L., Singh A.K., A comparison of prediction equations for estimating glomerular filtration rate in adults without kidney disease, Journal of the American Society of Nephrology, 14(10), 2573-2580, 2003. Search in Google Scholar

[15] Freedman B.S., Modeling Kidney Disease with iPS Cells: Supplementary Issue: Stem Cell Biology, Biomarker Insights, 10, BMI-S20054, 2015. Search in Google Scholar

[16] Umar M., Amin F., Wahab H.A., Baleanu D., Unsupervised constrained neural network modeling of boundary value corneal model for eye surgery, Applied Soft Computing, 85, 105826, 2019. Search in Google Scholar

[17] Wang Y., Zhao T., Liu J., Viral dynamics of an HIV stochastic model with cell-to-cell infection, CTL immune response and distributed delays, Mathematical Biosciences and Engineering, 16(6), 7126-7154, 2019. Search in Google Scholar

[18] Verma A., Kumar M., Numerical solution of third-order Emden-Fowler type equations using artificial neural network technique, The European Physical Journal Plus, 135(751), 1-14, 2020. Search in Google Scholar

[19] Tambaru D., Djahi B.S., Ndii M.Z., The effects of hard water consumption on kidney function: insights from mathematical modelling, AIP Conference Proceedings, 1937(1), 020020, 2018. Search in Google Scholar

[20] Harris D.C., Quantitative chemical analysis, Macmillan, UK, 2010. Search in Google Scholar