1. Peeri NC, Shrestha N, Rahman MS, et al. The SARS, MERS, and novel coronavirus (COVID-19) epidemics, the newest and biggest global health threats: what lessons have we learned? Int J Epidemiol. 2020; 49(3):717-26 [
DOI:10.1093/ije/dyaa033]
2. Qiu H, Wu J, Hong L, Luo Y, Song Q, Chen D. Clinical and epidemiological features of 36 children with coronavirus disease 2019 (COVID-19) in Zhejiang, China: an observational cohort study. The Lancet Infect Dis. 2020. [
DOI:10.1016/S1473-3099(20)30198-5]
3. Shi H, Han X, Jiang N, et al. Radiological findings from 81 patients with COVID-19 pneumonia in Wuhan, China: a descriptive study. Lancet Infect Dis. 2020; 20(4):425-434 [
DOI:10.1016/S1473-3099(20)30086-4]
4. Cascella M, Rajnik M, Cuomo A, Dulebohn SC, Di Napoli R. Features, evaluation and treatment coronavirus (COVID-19). Statpearls [internet]: StatPearls Publishing; 2020.
5. Sohrabi C, Alsafi Z, O'Neill N, et al. World Health Organization declares global emergency: A review of the 2019 novel coronavirus (COVID-19). Int J Surg. 2020;76:71-76 [
DOI:10.1016/j.ijsu.2020.02.034]
6. Wang K, Kang S, Tian R, Zhang X, Wang Y. Imaging manifestations and diagnostic value of chest CT of coronavirus disease 2019 (COVID-19) in the Xiaogan area. Clin Radiol. 2020;75(5):341-47 [
DOI:10.1016/j.crad.2020.03.004]
7. Liu Y, Wang Z, Ren J, et al. A COVID-19 risk assessment decision support system for general practitioners: design and development study. J Med Internet Res. 2020;22(6):e19786. [
DOI:10.2196/19786]
8. Yuan J, Zou R, Zeng L, et al. The correlation between viral clearance and biochemical outcomes of 94 COVID-19 infected discharged patients. Inflamm Res. 2020:1-8. [
DOI:10.1007/s00011-020-01342-0]
9. Bai L, Yang D, Wang X, et al. Chinese experts' consensus on the internet of things-aided diagnosis and treatment of coronavirus disease 2019. Clinical eHealth. 2020;3:7-15 [
DOI:10.1016/j.ceh.2020.03.001]
10. Bayram M, Springer S, Garvey CK, Özdemir V. COVID-19 digital health innovation policy: A portal to alternative futures in the making. OMICS: J Integ Biol. 2020;24(8):460-69 [
DOI:10.1089/omi.2020.0089]
11. Ma LL, Li BH, Jin YH, Deng T, Ren XQ, Zeng XT. Developments, evolution, and implications of national diagnostic criteria for COVID-19 in china. Front Med. 2020;7:242. [
DOI:10.3389/fmed.2020.00242]
12. Mahmood A, Gajula C, Gajula P. Clinical and diagnostic criteria of COVID 19; a study of 4659 patients evaluating diagnostic testing and establishing an algorithm. J Med Surg Sci. 2020;2:2.
13. Shipe ME, Deppen SA, Farjah F, Grogan EL. Developing prediction models for clinical use using logistic regression: an overview. J Thoracic Dis. 2019;11(Suppl 4): S574. [
DOI:10.21037/jtd.2019.01.25]
14. Agbehadji IE, Awuzie BO, Ngowi AB, Millham RC. Review of big data analytics, artificial intelligence, and nature-inspired computing models towards accurate detection of COVID-19 pandemic cases and contact tracing. Int J Environ Res Public Health. 2020;17(15). [
DOI:10.3390/ijerph17155330]
15. Haleem A, Javaid M, Khan IH, Vaishya R. Significant applications of big data in COVID-19 pandemic. Indian J Orthopaedics. 2020;54(4):526-8. [
DOI:10.1007/s43465-020-00129-z]
16. Briz-Redon A, Serrano-Aroca A. The effect of climate on the spread of the COVID-19 pandemic: A review of findings, and statistical and modeling techniques. Earth and Environment.2020;44(5):591-604 [
DOI:10.1177/0309133320946302]
17. Rehm GB, Woo SH, Chen XL, et al. Leveraging IoTs and machine learning for patient diagnosis and ventilation management in the intensive care unit. IEEE Pervasive Computing. 2020. [
DOI:10.1109/MPRV.2020.2986767]
18. Sarkodie SA, Owusu PA. Investigating the cases of novel coronavirus disease (COVID-19) in China using dynamic statistical techniques. Heliyon. 2020;6(4): e03747 [
DOI:10.1016/j.heliyon.2020.e03747]
19. Kanagarathinam K, Sekar K. Estimation of the reproduction number and early prediction of the COVID-19 outbreak in India using a statistical computing approach. Epidemiol Health. 2020;42. [
DOI:10.4178/epih.e2020028]
20. Mohammed MA, Abdulkareem KH, Al-Waisy AS, et al. Benchmarking methodology for selection of optimal COVID-19 diagnostic model based on entropy and TOPSIS methods. IEEE Access. 2020. [
DOI:10.1109/ACCESS.2020.2995597]
21. Alom MZ, Rahman M, Nasrin MS, Taha TM, Asari VK. COVID_MTNet: COVID-19 detection with multi-task deep learning approaches. arXiv preprint arXiv:200403747. 2020.
22. Hussain A, Bhowmik B, do Vale Moreira NC. COVID-19 and diabetes: Knowledge in progress. Diabet Res Clin Pract. 2020;162. [
DOI:10.1016/j.diabres.2020.108142]
23. Moujaess E, Kourie HR, Ghosn M. Cancer patients and research during COVID-19 pandemic: A systematic review of current evidence. Criti Rev Oncol Hematol. 2020;150:102972. [
DOI:10.1016/j.critrevonc.2020.102972]
24. Deeks JJ, Dinnes J, Takwoingi Y, et al. Diagnosis of SARS-CoV-2 infection and COVID-19: accuracy of signs and symptoms; molecular, antigen, and antibody tests; and routine laboratory markers. Cochrane Database of Systematic Reviews. 2020;2020(4). [
DOI:10.1002/14651858.CD013596]
25. Iser BPM, Sliva I, Raymundo VT, Poleto MB, Schulter-Trevisol F, Bobinski F. Suspected COVID-19 case definition: a narrative review of the most frequent signs and symptoms among confirmed cases. Epidemiologia e servicos de saude : revista do Sistema Unico de Saude do Brasil. 2020;29(3):e2020233. [
DOI:10.5123/S1679-49742020000300018]
26. Jutzeler CR, Bourguignon L, Weis CV, et al. Comorbidities, clinical signs and symptoms, laboratory findings, imaging features, treatment strategies, and outcomes in adult and pediatric patients with COVID-19: A systematic review and meta-analysis. Travel Med Infect Dis. 2020;37: 101825 [
DOI:10.1016/j.tmaid.2020.101825]
27. Struyf T, Deeks JJ, Dinnes J, et al. Signs and symptoms to determine if a patient presenting in primary care or hospital outpatient settings has COVID-19 disease. Cochrane Database Syst Rev. 2020;2020(7): CD013665 [
DOI:10.1002/14651858.CD013665]
28. Almeshal AM, Almazrouee AI, Alenizi MR, Alhajeri SN. Forecasting the spread of COVID-19 in Kuwait using compartmental and logistic regression models. Apply Sci. 2020;10(10):3402. [
DOI:10.3390/app10103402]
29. Chretien JP, George D, Shaman J, Chitale RA, McKenzie FE. Influenza forecasting in human populations: A scoping review. PLOS ONE. 2014;9(4):e94130. [
DOI:10.1371/journal.pone.0094130]
30. Udhaya Kumar S, Thirumal Kumar D, Prabhu Christopher B, George Priya Doss C. The rise and impact of COVID-19 in India. Front Med. 2020;7:250 [
DOI:10.3389/fmed.2020.00250]
31. Ng QX, De Deyn MLZQ, Loke W, Chan HW. A framework to deal with uncertainty in the age of COVID-19. Asian J Psychiatr. 2020;54: 102263 [
DOI:10.1016/j.ajp.2020.102263]
32. Chater N. Facing up to the uncertainties of COVID-19. Nature Human Behav. 2020;4(5):439. [
DOI:10.1038/s41562-020-0865-2]
33. Zhang G, Hu C, Luo L, et al. Clinical features and short-term outcomes of 221 patients with COVID-19 in Wuhan, China. J Clin Virol. 2020:104364. [
DOI:10.1016/j.jcv.2020.104364]