A Web Portal for Real-Time Data Quality Analysis on the Brazilian Tuberculosis Research Network: A Case Study

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Computational Science – ICCS 2023 (ICCS 2023)

Abstract

Research projects with Tuberculosis clinical data generate large volumes of complex data, requiring sophisticated tools to create processing pipelines to extract meaningful insights. However, creating this type of tool is a complex and costly task, especially for researchers who need to gain experience with technology or statistical analysis. In this work, we present a web portal that can connect to any database, providing easy access to statistical analysis of the clinical data in real-time using charts, tables, or any other data visualization technique. The tool is user-friendly and customizable, reaching the project’s needs according to its particularities. The developed portal in this work was used as a use case for the research project developed by the Federal University of Rio de Janeiro (UFRJ) for the validation and cost of performance of the Line Probe Assay 1 and 2 (LPA) as a method of diagnosing resistant Tuberculosis in Brazilian’s reference centers. In the use case, the tool proved to be a valuable resource for researchers, bringing efficiency and effectiveness in analyzing results for quick and correct clinical data interpretation.

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Acknowledgments

The study was partially supported by the Brazilian National Council for Scientific and Technological Development (CNPq) - grant numbers 440758/2018-1, 22411-2019, coordinated by author A.K., and by the São Paulo Research Foundation (FAPESP) - grant number 2020/ 01975-9, coordinated by author D.A.

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Correspondence to Victor Cassão .

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Cassão, V. et al. (2023). A Web Portal for Real-Time Data Quality Analysis on the Brazilian Tuberculosis Research Network: A Case Study. In: Mikyška, J., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M. (eds) Computational Science – ICCS 2023. ICCS 2023. Lecture Notes in Computer Science, vol 10475. Springer, Cham. https://doi.org/10.1007/978-3-031-36024-4_24

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  • DOI: https://doi.org/10.1007/978-3-031-36024-4_24

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