{"title":"Analysis of Protein in Diet vs COVID-19 with Machine Learning","authors":"Tianzhe Fang, Yuheng Shi, Beining Mu","doi":"10.1109/ITCA52113.2020.00020","DOIUrl":null,"url":null,"abstract":"From the first month in 2020, the coronavirus COVID-19 has swept the whole world like a hurricane, which caused a huge number of deaths around the world. There are a lot of different kinds of research on this pandemic. Because the health diet plays an important role in our immune system, which is contributed to the defense of the virus and the recovery after the treatment, this study aims to determine the relationships between the protein quantity in food and COVID-19. To find the correlation between them, we decide to use a basic regression as an analyzing tool to deal with it. To find the relationship between the quantity of protein in diet and COVID-19, we did the investigation first to find a proper dataset and a proper machine learning model. We tried to explore and investigate whether the protein in food is related to the recovery and death rate of COVID-19. By analyzing the data, we found that there is almost no correlation between the two. It seems the quantity of the protein plays a small role in the recuperation of COVID-19, however, there are many other factors, such as other nutritional elements, people’s age, gender, and their underlying disease types, etc., which all affect their recovery status of COVID-19. We need more information for our research and update or change a more proper model for it.","PeriodicalId":103309,"journal":{"name":"2020 2nd International Conference on Information Technology and Computer Application (ITCA)","volume":"117 25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 2nd International Conference on Information Technology and Computer Application (ITCA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITCA52113.2020.00020","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
From the first month in 2020, the coronavirus COVID-19 has swept the whole world like a hurricane, which caused a huge number of deaths around the world. There are a lot of different kinds of research on this pandemic. Because the health diet plays an important role in our immune system, which is contributed to the defense of the virus and the recovery after the treatment, this study aims to determine the relationships between the protein quantity in food and COVID-19. To find the correlation between them, we decide to use a basic regression as an analyzing tool to deal with it. To find the relationship between the quantity of protein in diet and COVID-19, we did the investigation first to find a proper dataset and a proper machine learning model. We tried to explore and investigate whether the protein in food is related to the recovery and death rate of COVID-19. By analyzing the data, we found that there is almost no correlation between the two. It seems the quantity of the protein plays a small role in the recuperation of COVID-19, however, there are many other factors, such as other nutritional elements, people’s age, gender, and their underlying disease types, etc., which all affect their recovery status of COVID-19. We need more information for our research and update or change a more proper model for it.