Bender C, Ghosh A, Vakili H, Ghosh P, Ghosh A
Biophys Rep (N Y). 2024; 4(4):100182.
PMID: 39270798
PMC: 11775906.
DOI: 10.1016/j.bpr.2024.100182.
Hu C
Nat Prod Bioprospect. 2024; 14(1):12.
PMID: 38282092
PMC: 10822835.
DOI: 10.1007/s13659-024-00432-4.
Zhang Q, Wang M, Han C, Wen Z, Meng X, Qi D
Vaccines (Basel). 2023; 11(3).
PMID: 36992256
PMC: 10058540.
DOI: 10.3390/vaccines11030673.
Shahabi N, Mohseni S, Dadipoor S, Rad R, Hassani L
Health Sci Rep. 2022; 6(1):e993.
PMID: 36523448
PMC: 9748409.
DOI: 10.1002/hsr2.993.
Pal D, Ghosh D, Santra P, Mahapatra G
Biophysics (Oxf). 2022; 67(2):231-244.
PMID: 35789554
PMC: 9244063.
DOI: 10.1134/S0006350922020154.
An Investigation on Chinese Public Acceptance of COVID-19 Prevention Measures.
Zhang A, Yang H, Tong S, Gao J
Int J Environ Res Public Health. 2022; 19(9).
PMID: 35564482
PMC: 9102455.
DOI: 10.3390/ijerph19095087.
A model for the spread of infectious diseases compatible with case data.
Huang N, Qiao F, Wang Q, Qian H, Tung K
Proc Math Phys Eng Sci. 2022; 477(2254):20210551.
PMID: 35153589
PMC: 8511757.
DOI: 10.1098/rspa.2021.0551.
AI Techniques for COVID-19.
Hussain A, Bouachir O, Al-Turjman F, Aloqaily M
IEEE Access. 2022; 8:128776-128795.
PMID: 34976554
PMC: 8545328.
DOI: 10.1109/ACCESS.2020.3007939.
Resetting the Initial Conditions for Calculating Epidemic Spread: COVID-19 Outbreak in Italy.
Babac M, Mornar V
IEEE Access. 2021; 8:148021-148030.
PMID: 34786281
PMC: 8545335.
DOI: 10.1109/ACCESS.2020.3015923.
Modeling and prediction of the transmission dynamics of COVID-19 based on the SINDy-LM method.
Jiang Y, Xiong X, Zhang S, Wang J, Li J, Du L
Nonlinear Dyn. 2021; 105(3):2775-2794.
PMID: 34312574
PMC: 8295551.
DOI: 10.1007/s11071-021-06707-6.
The Prediction for COVID-19 Outbreak in China by using the Concept of Term Structure for the Turning Period.
Yuan G, Di L, Yang Z, Qian G, Qian X, Zeng T
Procedia Comput Sci. 2021; 187:284-293.
PMID: 34149967
PMC: 8197400.
DOI: 10.1016/j.procs.2021.04.064.
Fractional stochastic models for COVID-19: Case study of Egypt.
Omar O, Elbarkouky R, Ahmed H
Results Phys. 2021; 23:104018.
PMID: 33728261
PMC: 7952136.
DOI: 10.1016/j.rinp.2021.104018.
A stochastic numerical analysis based on hybrid NAR-RBFs networks nonlinear SITR model for novel COVID-19 dynamics.
Shoaib M, Raja M, Sabir M, Bukhari A, Alrabaiah H, Shah Z
Comput Methods Programs Biomed. 2021; 202:105973.
PMID: 33610034
PMC: 7868062.
DOI: 10.1016/j.cmpb.2021.105973.
A simple transmission dynamics model for predicting the evolution of COVID-19 under control measures in China.
Shang C, Yang Y, Chen G, Shang X
Epidemiol Infect. 2021; 149:e43.
PMID: 33563354
PMC: 7900669.
DOI: 10.1017/S0950268821000339.
ALeRT-COVID: Attentive Lockdown-awaRe Transfer Learning for Predicting COVID-19 Pandemics in Different Countries.
Li Y, Jia W, Wang J, Guo J, Liu Q, Li X
J Healthc Inform Res. 2021; 5(1):98-113.
PMID: 33426422
PMC: 7786857.
DOI: 10.1007/s41666-020-00088-y.
Prediction of the COVID-19 epidemic trends based on SEIR and AI models.
Feng S, Feng Z, Ling C, Chang C, Feng Z
PLoS One. 2021; 16(1):e0245101.
PMID: 33417605
PMC: 7793264.
DOI: 10.1371/journal.pone.0245101.
A multivariate data analysis approach for investigating daily statistics of countries affected with COVID-19 pandemic.
Ramadan A, Kamel A, Taha A, El-Shabrawy A, Anwar Abdel-Fatah N
Heliyon. 2020; 6(11):e05575.
PMID: 33251372
PMC: 7685045.
DOI: 10.1016/j.heliyon.2020.e05575.
Estimation of SIR model's parameters of COVID-19 in Algeria.
Lounis M, Bagal D
Bull Natl Res Cent. 2020; 44(1):180.
PMID: 33100825
PMC: 7570398.
DOI: 10.1186/s42269-020-00434-5.
Predicting and analyzing the COVID-19 epidemic in China: Based on SEIRD, LSTM and GWR models.
Liu F, Wang J, Liu J, Li Y, Liu D, Tong J
PLoS One. 2020; 15(8):e0238280.
PMID: 32853285
PMC: 7451659.
DOI: 10.1371/journal.pone.0238280.
Data driven estimation of novel COVID-19 transmission risks through hybrid soft-computing techniques.
Bhardwaj R, Bangia A
Chaos Solitons Fractals. 2020; 140:110152.
PMID: 32834640
PMC: 7381942.
DOI: 10.1016/j.chaos.2020.110152.