Declaration of Conflict of Interest: No conflict of interest is declared by author(s).

• Anderson RM, Heesterbeek H, Klinkenberg D, Hollingsworth TD. How will country-based mitigation measures influence the course of the COVID-19 epidemic?. The Lancet. 2020. https://doi.org/10.1016/S0140-6736(20)30567-5
• World Health Organization. Available at: https://www.who.int/
• Xu X, Chen P, Wang J, Feng J, Zhou H, Li X, et al. Evolution of the novel coronavirus from the ongoing Wuhan outbreak and modeling of its spike protein for risk of human transmission. Science China Life Sciences, 2020;63(3):457-60. https://doi.org/10.1007/s11427-020-1637-5 PMid: 32009228 PMCid:PMC7089049
• Huang C, Wang Y, Li X, Ren L, Zhao J, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. The Lancet, 2020;395(10223):497-506. https://doi.org/10.1016/S0140-6736(20)30183-5
• Majumder P, Majumder M, Saha AK, Sarkar K, Nath S. Real time reliability monitoring of hydro‐power plant by combined cognitive decision‐making technique. International Journal of Energy Research. 2019. https://doi.org/10.1002/er.4530
• Majumder P, Saha AK, Majumder M. A mathematical approach of exploration towards extreme risk factor in cancer of optimal condition. International Journal of Pharmaceutical Sciences and Research, 2018;9(9):3732-42. https://doi.org/10.13040/IJPSR.0975-8232.9(9).3732-42
• Majumder P, Saha AK, Majumder M. Evaluation of hydropower plants with respect to cost incurred by fuzzy decision making. Journal of civil and construction Engineering, 2016;2(3). Available at: http://matjournals.in/index.php/JOCCE/article/view/962
• Hwang CL, Yoon K. Methods for multiple attribute decision making. In Multiple attribute decision making (pp. 58-191). Springer, Berlin, Heidelberg. 1981. https://doi.org/10.1007/978-3-642-48318-9_3
• Jahanshahloo GR, Lotfi FH, Izadikhah M. An algorithmic method to extend TOPSIS for decision-making problems with interval data. Applied mathematics and computation, 2006;175(2):1375-84. https://doi.org/10.1016/j.amc.2005.08.048
• Chu TC, Lin YC. An interval arithmetic based fuzzy TOPSIS model. Expert Systems with Applications, 2009;36(8):10870-6. https://doi.org/10.1016/j.eswa.2009.01.083
• Ozdemir H, Bird D. Evaluation of morphometric parameters of drainage networks derived from topographic maps and DEM in point of floods. Environmental Geology, 2009;56(7):1405-15. https://doi.org/10.1007/s00254-008-1235-y
• Opricovic S, Tzeng GH. Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European journal of operational research, 2004;156(2):445-55. https://doi.org/10.1016/S0377-2217(03)00020-1
• Coronavirus Disease (COVID-19) – Statistics and Research. Available at: https://ourworldindata.org/coronavirus
• Nariman-Zadeh N, Darvizeh A, Darvizeh M, Gharababaei H. Modelling of explosive cutting process of plates using GMDH-type neural network and singular value decomposition. Journal of Materials Processing Technology, 2002;128(1-3):80-7. https://doi.org/10.1016/S0924-0136(02)00264-9
• Yeh CH, Deng H, Chang YH. Fuzzy multicriteria analysis for performance evaluation of bus companies. European Journal of Operational Research, 2000;126(3):459-73. https://doi.org/10.1016/S0377-2217(99)00315-X
• Lemke F, Müller JA. Self-organising data mining. Systems analysis modelling simulation, 2003;43(2):231-40. https://doi.org/10.1080/0232929031000136135
• Farlow SJ. Self-organizing methods in modeling: GMDH type algorithms (Vol. 54). CrC Press. 1984.
• Nariman-Zadeh N, Darvizeh A, Jamali A, Moeini A. Evolutionary design of generalized polynomial neural networks for modelling and prediction of explosive forming process. Journal of Materials Processing Technology, 2005;164:1561-71. https://doi.org/10.1016/j.jmatprotec.2005.02.020
• Gang W, Wang J. Predictive ANN models of ground heat exchanger for the control of hybrid ground source heat pump systems. Applied energy, 2013;112:1146-53. https://doi.org/10.1016/j.apenergy.2012.12.031
• Buratti C, Barelli L, Moretti E. Application of artificial neural network to predict thermal transmittance of wooden windows. Applied energy, 2012;98:425-32. https://doi.org/10.1016/j.apenergy.2012.04.004
• Kalogirou SA. Applications of artificial neural-networks for energy systems. Applied energy, 2000;67(1-2):17-35. https://doi.org/10.1016/S0306-2619(00)00005-2
• Sözen A, Arcaklioǧlu E, Özalp M, Kanit EG. Use of artificial neural networks for mapping of solar potential in Turkey. Applied Energy, 2004;77(3):273-86. https://doi.org/10.1016/S0306-2619(03)00137-5
• Kar S, Sharma KD, Maitra M. Gene selection from microarray gene expression data for classification of cancer subgroups employing PSO and adaptive K-nearest neighborhood technique. Expert Systems with Applications, 2015;42(1):612-27. https://doi.org/10.1016/j.eswa.2014.08.014
• Cliver DO. Control of viral contamination of food and environment. Food and Environmental Virology, 2009;1(1):3-9. https://doi.org/10.1007/s12560-008-9005-2 PMCid:PMC7090503
• Jin YH, Cai L, Cheng ZS, Cheng H, Deng T, et al. A rapid advice guideline for the diagnosis and treatment of 2019 novel coronavirus (2019-nCoV) infected pneumonia (standard version). Military Medical Research, 2020;7(1):4. https://doi.org/10.1186/s40779-020-0233-6 PMid:32029004 PMCid:PMC7003341
• Han Y, Yang H. The transmission and diagnosis of 2019 novel coronavirus infection disease (COVID‐19): A Chinese perspective. Journal of Medical Virology. 2020. https://doi.org/10.1002/jmv.25749 PMid:32141619

Vancouver

Majumder P, Biswas P, Majumder S. Application of New TOPSIS Approach to Identify the Most Significant Risk Factor and Continuous Monitoring of Death of COVID-19. Electron J Gen Med. 2020;17(6):em234. https://doi.org/10.29333/ejgm/7904

APA

Majumder, P., Biswas, P., & Majumder, S. (2020). Application of New TOPSIS Approach to Identify the Most Significant Risk Factor and Continuous Monitoring of Death of COVID-19. Electronic Journal of General Medicine, 17(6), em234. https://doi.org/10.29333/ejgm/7904

AMA

Majumder P, Biswas P, Majumder S. Application of New TOPSIS Approach to Identify the Most Significant Risk Factor and Continuous Monitoring of Death of COVID-19. Electron J Gen Med. 2020;17(6), em234. https://doi.org/10.29333/ejgm/7904

Chicago

Majumder, Priyanka, Piyali Biswas, and Srestha Majumder. "Application of New TOPSIS Approach to Identify the Most Significant Risk Factor and Continuous Monitoring of Death of COVID-19". Electronic Journal of General Medicine 2020 17 no. 6 (2020): em234. https://doi.org/10.29333/ejgm/7904

Harvard

Majumder, P., Biswas, P., and Majumder, S. (2020). Application of New TOPSIS Approach to Identify the Most Significant Risk Factor and Continuous Monitoring of Death of COVID-19. Electronic Journal of General Medicine, 17(6), em234. https://doi.org/10.29333/ejgm/7904

MLA

Majumder, Priyanka et al. "Application of New TOPSIS Approach to Identify the Most Significant Risk Factor and Continuous Monitoring of Death of COVID-19". Electronic Journal of General Medicine, vol. 17, no. 6, 2020, em234. https://doi.org/10.29333/ejgm/7904