Application of principal component analysis on temporal evolution of COVID-19

Nobi, Ashadun; Tuhin, Kamrul Hasan; Lee, Jae Woo

doi:10.1371/journal.pone.0260899

Cited by 6 publications

(2 citation statements)

References 22 publications

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“…This new coronavirus strain is the seventh member of the coronaviridae family that can infect humans. It is a highly pathogenic and contagious virus, which prompted the WHO to declare it a public emergency of international concern on January 30th, 2020, and a pandemic by March 11th, 2020 [1,2]. Furthermore, by August 8th, 2022, there have been 591,407,978 confirmed cases of COVID-19 worldwide, with 6,442,204 reported deaths [3].…”

Section: Introductionmentioning

confidence: 99%

Nephrotic Syndrome in Adult Patients With COVID-19 Infection or Post COVID-19 Vaccine: A Systematic Review

Cancarevic¹,

Nassar²,

Medina³

et al. 2022

Cureus

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Nephrotic syndrome is a condition characterized by damage to podocytes that results in significant proteinuria, edema, hyperlipidemia, and hypercoagulability. Infections and malignancies are frequently associated with nephrotic syndrome. The COVID-19 virus has been associated with several atypical presentations of upper respiratory infections and acute kidney injury. Considering that COVID-19 causes systemic inflammatory changes, it seems plausible that it may also lead to nephrotic syndrome. This study aimed to investigate if an association between COVID-19 and the different types of nephrotic syndromes exists. Data were extracted into a spreadsheet. Statistical analysis was performed using Statistical Package for Social Sciences (SPSS, IBM Corp., Armonk, NY, USA).We performed a systematic search of PubMed/Medline and Embase databases using both medical subject headings (MeSH) and regular keywords associated with COVID-19 and nephrotic syndrome, including different types of nephrotic syndromes. The search was performed on 17th December 2021. We included case reports and case series about adult patients who developed findings suggestive of nephrotic syndrome shortly after infection or vaccination. We excluded cases involving children, pregnant women, articles written in languages other than English, and those that were not retrievable. The relevance and quality of identified articles were assessed.We included 32 articles in the study, primarily case reports and case series. In our study, COVID-19 and the COVID-19 vaccine have been associated with the development of nephrotic syndrome, primarily a collapsing form of focal segmental glomerulosclerosis, although other forms have been observed as well. There was little consistency in patient histories, clinical presentations, clinical courses, or treatment regimens, although it appeared that most cases eventually resolved. More cases need to be reported and analyzed before more definitive conclusions can be reached.In conclusion, nephrotic syndrome is a possible complication of both COVID-19 infection and the COVD-19 vaccine and should be considered in patients exhibiting sudden onset edemas or deterioration in kidney function. While the majority of cases respond to standard treatment, clearer guidelines will need to be developed once more data is available.

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Section: Introductionmentioning

confidence: 99%

Nephrotic Syndrome in Adult Patients With COVID-19 Infection or Post COVID-19 Vaccine: A Systematic Review

Cancarevic¹,

Nassar²,

Medina³

et al. 2022

Cureus

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“… GQ1, GQ2, SQ1, SQ3 Nobi et al. ( 2021 ) Bangladesh, South Korea Apply principal component analysis (PCA) to the correlations for the changes of cumulative time-series of COVID-19 death and confirmed cases between different countries GQ1, GQ2, SQ1, SQ3 Ohi et al. ( 2020 ) Bangladesh, Saudi Arabia Demonstrate what actions an agent (trained using reinforcement learning) may take in different possible pandemic scenarios depending on the spread of disease and economic factors.…”

Section: Resultsmentioning

confidence: 99%

Tracking machine learning models for pandemic scenarios: a systematic review of machine learning models that predict local and global evolution of pandemics

Palermo

Policarpo

Costa

et al. 2022

Netw Model Anal Health Inform Bioinforma

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This systematic review aims to study and classify machine learning models that predict pandemics’ evolution within affected regions or countries. The advantage of this systematic review is that it allows the health authorities to decide what prediction model fits best depending upon the region’s criticality and optimize hospitals’ approaches to preparing and anticipating patient care. We searched ACM Digital Library, Biomed Central, BioRxiv+MedRxiv, BMJ, Computers and Applied Sciences, IEEEXplore, JMIR Medical Informatics, Medline Daily Updates, Nature, Oxford Academic, PubMed, Sage Online, ScienceDirect, Scopus, SpringerLink, Web of Science, and Wiley Online Library between 1 January 2020 and 31 July 2022. We divided the interventions into similarities between cumulative COVID-19 real cases and machine learning prediction models’ ability to track pandemics trending. We included 45 studies that rated low to high risk of bias. The standardized mean differences (SMD) for the two groups were 0.18, 95% CI, with interval of [0.01, 0.35], =0, and p value=0.04. We built a taxonomic analysis of the included studies and determined two domains: pandemics trending prediction models and geolocation tracking models. We performed the meta-analysis and data synthesis and got low publication bias because of missing results. The level of certainty varied from very low to high. By submitting the 45 studies on the risk of bias, the levels of certainty, the summary of findings, and the statistical analysis via the forest and funnel plots assessments, we could determine the satisfactory statistical significance homogeneity across the included studies to simulate the progress of the pandemics and help the healthcare authorities to take preventive decisions.

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Optimized Vaccine Selection Using Machine Learning and Genetic Algorithms: A Study on Side Effects of COVID-19 Vaccines

Soni,

Joshi,

Deep

et al. 2024

Lecture Notes in Networks and Systems

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Application of principal component analysis on temporal evolution of COVID-19

Cited by 6 publications

References 22 publications

Nephrotic Syndrome in Adult Patients With COVID-19 Infection or Post COVID-19 Vaccine: A Systematic Review

Nephrotic Syndrome in Adult Patients With COVID-19 Infection or Post COVID-19 Vaccine: A Systematic Review

Tracking machine learning models for pandemic scenarios: a systematic review of machine learning models that predict local and global evolution of pandemics

Optimized Vaccine Selection Using Machine Learning and Genetic Algorithms: A Study on Side Effects of COVID-19 Vaccines

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