Application of Random Matrix Theory With Maximum Local Overlapping Semicircles for Comorbidity Analysis
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Abstract
In December 2019, the COVID-19 pandemic began, which has claimed the lives of millions of people around the world. This article presents a regional analysis of COVID-19 in Mexico. Due to comorbidities in Mexican society, this new pandemic implies a higher risk for the population. The study period runs from 12 April to 5 October 2020 761,665. This article proposes a unique methodology of random matrix theory in the moments of a probability measure that appears as the limit of the empirical spectral distribution by Wigner's semicircle law. The graphical presentation of the results is done with Machine Learning methods in the SuperHeat maps. With this, it was possible to analyze the behavior of patients who tested positive for COVID-19 and their comorbidities, with the conclusion that the most sensitive comorbidities in hospitalized patients are the following three: COPD, Other Diseases, and Renal Diseases.
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SciScore for 10.1101/2021.08.23.21262184: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank…
SciScore for 10.1101/2021.08.23.21262184: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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