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Neutrosophic Sets and Systems

Abstract

Therapeutic prediction response to probiotics in the field of inflammatory bowel disease (IBD) has been a struggle for the gastroenterology field of studies. However, as IBD increases in the general population and varying reports of treatment response due to heterogeneous use of probiotics suggests greater predictive need. In addition, based on the multitude of articles currently published correlating the gut microbiome with disease pathology, there remains a theoretical gap in the literature. That is, the application of neutrosophic statistics to simulate the uncertainties experienced by biological information and later clinical real world data. This article seeks to fill that gap by using neutrosophic regression to project and predict uncertainty associated with patient inflammatory markers and aspects of the microbiome. Furthermore, this study provides evidence that neutrosophic regression allows for accurate prediction without the shortcomings of standard statistics based on microbiome content, probiotic administration, and clinical findings. Thus, this article provides the reader with two advantages. First, a novel consideration for a previously non-comparable approach to analytic findings for personalized medicine approaches which could inform choice of probiotic treatment. Second, a predictive theory for future experimentation and analysis that champions the need to understand the immune response dynamics and subsequent microbiome manipulation capabilities in IBD. Therefore, this study is necessary for the progression of theoretical understanding within the gastroenterology field but more so, something practical which could lead to greater treatment options in the future.

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