Most scientific areas now use big data analysis to extract knowledge from complicated and massive databases. This method is now utilized in medicine to investigate big groups of individuals. This review helped to understand that the employed artificial intelligence and sophisticated machine learning approaches to investigate physio pathogenesis-based therapy in pSS. The procedure also estimated the evolution of trends in statistical techniques, cohort sizes, and the number of publications throughout this time span. In all, 44,077 abstracts and 1,017 publications were reviewed. The mean number of chosen articles each year was 101.0 (S.D. 19.16), but it climbed dramatically with time (from 74 articles in 2008 to 138 in 2017). Only 12 of them focused on pSS, but none on the topic of pathogenesis-based therapy. A thorough assessment of the literature over the last decade collected all papers reporting on the application of sophisticated statistical analysis in the study of systemic autoimmune disorders (SADs). To accomplish this job, an automatic bibliography screening approach has been devised.
To summarize, whereas medicine is gradually entering the era of big data analysis and artificial intelligence, these techniques are not yet being utilized to characterize pSS-specific pathogenesis-based treatment. Nonetheless, big multicenter studies using advanced algorithmic methods on large cohorts of SADs patients are studying this feature.
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