Supriya Khaitan, P. Shukla, Anamika Mitra, T. Poongodi, Rashi Agarwal
{"title":"利用机器学习实现数据可视化,有效跟踪大流行- COVID-19","authors":"Supriya Khaitan, P. Shukla, Anamika Mitra, T. Poongodi, Rashi Agarwal","doi":"10.1049/pbhe029e_ch17","DOIUrl":null,"url":null,"abstract":"From the first case in December 2019 to more than 2.92 million cases in just 3 months, COVID-19 became a pandemic. COVID-19 is spreading all around the world, and due to this pandemic situation, humans’ life is at risk. On one side, healthcare and sanitization workers are stretching themselves to deal with this situation at the frontline, and on the other, data scientists and machine learning (ML) experts are researching to provide data in an understandable form to the world. This chapter provides the details of different ways of processing and visualizing the huge amount data generated on this pandemic. This includes the clusters on the basis of symptoms in different age groups, effects of COVID-19 on different countries, etc. © The Institution of Engineering and Technology 2021.","PeriodicalId":433553,"journal":{"name":"Blockchain and Machine Learning for e-Healthcare Systems","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Data visualization using machine learning for efficient tracking of pandemic - COVID-19\",\"authors\":\"Supriya Khaitan, P. Shukla, Anamika Mitra, T. Poongodi, Rashi Agarwal\",\"doi\":\"10.1049/pbhe029e_ch17\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"From the first case in December 2019 to more than 2.92 million cases in just 3 months, COVID-19 became a pandemic. COVID-19 is spreading all around the world, and due to this pandemic situation, humans’ life is at risk. On one side, healthcare and sanitization workers are stretching themselves to deal with this situation at the frontline, and on the other, data scientists and machine learning (ML) experts are researching to provide data in an understandable form to the world. This chapter provides the details of different ways of processing and visualizing the huge amount data generated on this pandemic. This includes the clusters on the basis of symptoms in different age groups, effects of COVID-19 on different countries, etc. © The Institution of Engineering and Technology 2021.\",\"PeriodicalId\":433553,\"journal\":{\"name\":\"Blockchain and Machine Learning for e-Healthcare Systems\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Blockchain and Machine Learning for e-Healthcare Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1049/pbhe029e_ch17\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Blockchain and Machine Learning for e-Healthcare Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1049/pbhe029e_ch17","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Data visualization using machine learning for efficient tracking of pandemic - COVID-19
From the first case in December 2019 to more than 2.92 million cases in just 3 months, COVID-19 became a pandemic. COVID-19 is spreading all around the world, and due to this pandemic situation, humans’ life is at risk. On one side, healthcare and sanitization workers are stretching themselves to deal with this situation at the frontline, and on the other, data scientists and machine learning (ML) experts are researching to provide data in an understandable form to the world. This chapter provides the details of different ways of processing and visualizing the huge amount data generated on this pandemic. This includes the clusters on the basis of symptoms in different age groups, effects of COVID-19 on different countries, etc. © The Institution of Engineering and Technology 2021.