Muthusami RATHİNASAMY, Saritha KANDHASAMY

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Global Analysis of COVID-19 Clinical Related Trials

Objectives: The aim of this study was to analyze clinical trials using topic modelling to identify emerging vaccine progression topics around the globe. Methods: The most important computational problem for the modeling of topics is using the observed documents to infer the hidden topic structure. The topic model was developed on the basis of data recorded on the WHO International Clinical Trials Registry Platform (ICTRP) between 3 February and 11 August 2020. Results: Show the top 10 topics based on the topic model that has been created. These topics are explored in the reviews and studies of clinical trials related to the development of the COVID-19 vaccine. Conclusion: This study aimed at the clinical trials registered at ICTRP and showed the recorded monthly clinical trials as well as the top 15 countries vying for the COVID-19 vaccine from 3 February to 11 August 2020. Using the dataset of the collected clinical trials, the topic model was developed to examine emerging trends in vaccine progression. J Microbiol Infect Dis 2020; 10(4):xxxxx. Keywords: COVID-19, Clinical trials, Vaccine progression, Emerging topics, Topic model
Keywords:

COVID-19, Clinical trials, Vaccine progression Emerging topics, Topic model,

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  • 1. Huang C, Wang Y, Li X, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 2020; 395:497–506.
  • 2. World Health Organization. Coronavirus disease (COVID-19) Situation reports. 2020. https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports (Accessed 17 August 2020)
  • 3. World Health Organization. News room. 2020. https://www.who.int/news-room/detail/15-07-2020-more-than-150-countries-engaged-in-covid-19-vaccine-global-access-facility (Accessed 21 August 2020)
  • 4. World Health Organization. Draft landscape of COVID-19 candidate vaccines. 2020. https://www.who.int/publications/m/item/draft-landscape-of-covid-19-candidate-vaccines (Accessed 21 August 2020)
  • 5. Long L, Zeng X, Zhang X, et al. Short-term outcomes of COVID-19 and risk factors for progression. Eur Respir J 2020; 55: 2000990. doi.org/10.1183/13993003.00990-2020.
  • 6. Xu PP, Tian R, Luo S, et al. Risk factors for adverse clinical outcomes with COVID-19 in China: a multicenter, retrospective, observational study. Theranostics 2020; 10(14): 6372- 6383. doi: 10.7150/thno.46833
  • 7. Biswas PS et al., A systematic review and Meta-analysis of clinical and laboratory findings of COVID-19, J Microbiol Infect Dis 2020; 10(3):121-135.
  • 8. Julie M, et al., Searching ClinicalTrials.gov and the International Clinical Trials Registry Platform to inform systematic reviews: what are the optimal search approaches? J Med Libr Assoc. 2014; 102(3): 177–183. doi: 10.3163/1536-5050.102.3.007
  • 9. Blei DM. Probabilistic topic models. Communications of the ACM 2012; 55(4): 77-84. 10.1145/2133806.2133826
Journal of Microbiology and Infectious Diseases-Cover
  • ISSN: 2146-3158
  • Başlangıç: 2011
  • Yayıncı: Sağlık Araştırmaları Derneği
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