Evaluation of Country Dietary Habits Using Machine Learning Techniques in Relation to Deaths from COVID-19

Garcí­a-Ordás, María Teresa; Ramos, Natalia Arias; Benavides, Carmen; García-Olalla, Oscar; Bení­tez-Andrades, José Alberto

doi:10.3390/healthcare8040371

Cited by 13 publications

(11 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The research findings stated that countries with the highest death ratio were those who had a high consumption of fats, while countries with a lower death rate have a higher level of cereal consumption followed by a lower total average intake of kilocalories (García-Ordás, et al (2020)). A study conducted to (Shinwoo et al 2020) their research data were extracted from the immigrant Korean COVID-19 patients who were 290 cases from 12 states all of them older than 18 years, the study observed the ability to the prediction of discrimination-related variables, such as racism effects, and sociodemographic factors that influence the psychological distress level during the COVID-19 pandemic, they nominated the supervised learning as the method and then using the Artificial Neural Network ANN as the main algorithm, their result showed The Artificial Neural Network (ANN) analysis, which is a statistical model and able to examine complex non-linear interactions of variables, was applied.…”

Section: Discussionmentioning

confidence: 92%

Coronavirus disease (COVID-19) cases analysis using machine-learning applications

2021

View full text Add to dashboard Cite

Today world thinks about coronavirus disease that which means all even this pandemic disease is not unique. The purpose of this study is to detect the role of machine-learning applications and algorithms in investigating and various purposes that deals with COVID-19. Review of the studies that had been published during 2020 and were related to this topic by seeking in Science Direct, Springer, Hindawi, and MDPI using COVID-19, machine learning, supervised learning, and unsupervised learning as keywords. The total articles obtained were 16,306 overall but after limitation; only 14 researches of these articles were included in this study. Our findings show that machine learning can produce an important role in COVID-19 investigations, prediction, and discrimination. In conclusion, machine learning can be involved in the health provider programs and plans to assess and triage the COVID-19 cases. Supervised learning showed better results than other Unsupervised learning algorithms by having 92.9% testing accuracy. In the future recurrent supervised learning can be utilized for superior accuracy.

show abstract

Section: Discussionmentioning

confidence: 92%

Coronavirus disease (COVID-19) cases analysis using machine-learning applications

2021

View full text Add to dashboard Cite

show abstract

“…The latter [ 28 ] and hyperinsulinemia [ 70 ] play a crucial role in thrombo-inflammation during COVID-19 infection. Countries with higher and lower death rates for COVID-19 appear to have high consumptions of fats and cereal, respectively [ 71 ]. Hyperglycemia and Reactive Oxygen Species (ROS)-induced oxidation of carbohydrates generate the adduct derivatives advanced glycation end products (AGE) [ 72 ].…”

Section: Diabesity Meta-inflammation and Il-6: The Role In Severmentioning

confidence: 99%

Mediterranean Diet for the Prevention of Gestational Diabetes in the Covid-19 Era: Implications of Il-6 In Diabesity

Fedullo¹,

Schiattarella

Morlando

et al. 2021

IJMS

View full text Add to dashboard Cite

The aim of this review is to highlight the influence of the Mediterranean Diet (MedDiet) on Gestational Diabetes Mellitus (GDM) and Gestational Weight Gain (GWG) during the COVID-19 pandemic era and the specific role of interleukin (IL)-6 in diabesity. It is known that diabetes, high body mass index, high glycated hemoglobin and raised serum IL-6 levels are predictive of poor outcomes in coronavirus disease 2019 (COVID-19). The immunopathological mechanisms of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection include rising levels of several cytokines and in particular IL-6. The latter is associated with hyperglycemia and insulin resistance and could be useful for predicting the development of GDM. Rich in omega-3 polyunsaturated fatty acids, vitamins, and minerals, MedDiet improves the immune system and could modulate IL-6, C reactive protein and Nuclear Factor (NF)-κB. Moreover, polyphenols could modulate microbiota composition, inhibit the NF-κB pathway, lower IL-6, and upregulate antioxidant enzymes. Finally, adhering to the MedDiet prior to and during pregnancy could have a protective effect, reducing GWG and the risk of GDM, as well as improving the immune response to viral infections such as COVID-19.

show abstract

“…Various aspects of this pandemic are data-driven, including infection diagnosis based on CT scans of patients [ 1 , 2 ] or other symptoms [ 3 ], infection diagnosis based on metabolomics [ 4 ] and serologic data [ 5 , 6 ], epidemiologic analysis [ 7 , 8 ] and predictions [ 9 ], viral genetics [ 10 ] and host epigenetics studies [ 11 ], evolutionary path discovery [ 12 ], contact tracing [ 13 ] and quarantine enforcing [ 13 ], and numerous other aspects [ 14 ].…”

Section: Introductionmentioning

confidence: 99%

COVID and nutrition: A machine learning perspective

Jafari

Besharati

Izadi

et al. 2022

Informatics in Medicine Unlocked

View full text Add to dashboard Cite

A self-report questionnaire survey was conducted online to collect big data from over 16000 Iranian families (who were the residents of 1000 urban and rural areas of Iran). The resulting data storage contained over 1M records of data and over 1G records of automatically inferred information. Based on this data storage, a series of machine learning experiments was conducted to investigate the relationship between nutrition and the risk of contracting COVID-19. With highly accurate scores, the findings strongly suggest that foods and water sources containing certain natural bioactive and phytochemical agents may help to reduce the risk of apparent COVID-19 infection.

show abstract

Evaluation of Country Dietary Habits Using Machine Learning Techniques in Relation to Deaths from COVID-19

Cited by 13 publications

References 28 publications

Coronavirus disease (COVID-19) cases analysis using machine-learning applications

Coronavirus disease (COVID-19) cases analysis using machine-learning applications

Mediterranean Diet for the Prevention of Gestational Diabetes in the Covid-19 Era: Implications of Il-6 In Diabesity

COVID and nutrition: A machine learning perspective

Contact Info

Product

Resources

About