{"title":"加尔各答非传染性疾病影响的大数据分析框架","authors":"Supratim Bhattacharya, Jayanta Poray, Priyanka Debnath","doi":"10.1109/ICCECE48148.2020.9223099","DOIUrl":null,"url":null,"abstract":"Considering the gradual progress of urbanization, urban health has now become as one of the most challenging task for the current decade in India. An exhaustive and harmonize effect has been initiated at the national level in order to standardize the service and initiate the challenge to put every health services across the country under a single umbrella. In the last decade, various socio-demographic factors forced to make a transitional shift towards non-communicable diseases which has significantly increases the number of health loss. City like Kolkata also faced the same challenges. Large archieve of unstructured health data furnish vital statistical measure on public health and valuable insight into different determinants of communicable & non-communicable diseases. The integration of various data sources along with analytical algorithm is used to assess risk factors and localized vulnerability to assist in developing effective prevention and control strategies for different diseases and to optimize allocation of limited public health resources. We propose an analytical framework based on multiple correlation, Gini Index and multiple Regression technique for analysing different causes related to NCD burden in Kolkata.","PeriodicalId":129001,"journal":{"name":"2020 International Conference on Computer, Electrical & Communication Engineering (ICCECE)","volume":"149 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A BigData Analytics Framework on the Impact of Non Communicable Diseases in Kolkata\",\"authors\":\"Supratim Bhattacharya, Jayanta Poray, Priyanka Debnath\",\"doi\":\"10.1109/ICCECE48148.2020.9223099\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Considering the gradual progress of urbanization, urban health has now become as one of the most challenging task for the current decade in India. An exhaustive and harmonize effect has been initiated at the national level in order to standardize the service and initiate the challenge to put every health services across the country under a single umbrella. In the last decade, various socio-demographic factors forced to make a transitional shift towards non-communicable diseases which has significantly increases the number of health loss. City like Kolkata also faced the same challenges. Large archieve of unstructured health data furnish vital statistical measure on public health and valuable insight into different determinants of communicable & non-communicable diseases. The integration of various data sources along with analytical algorithm is used to assess risk factors and localized vulnerability to assist in developing effective prevention and control strategies for different diseases and to optimize allocation of limited public health resources. We propose an analytical framework based on multiple correlation, Gini Index and multiple Regression technique for analysing different causes related to NCD burden in Kolkata.\",\"PeriodicalId\":129001,\"journal\":{\"name\":\"2020 International Conference on Computer, Electrical & Communication Engineering (ICCECE)\",\"volume\":\"149 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Conference on Computer, Electrical & Communication Engineering (ICCECE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCECE48148.2020.9223099\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on Computer, Electrical & Communication Engineering (ICCECE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCECE48148.2020.9223099","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A BigData Analytics Framework on the Impact of Non Communicable Diseases in Kolkata
Considering the gradual progress of urbanization, urban health has now become as one of the most challenging task for the current decade in India. An exhaustive and harmonize effect has been initiated at the national level in order to standardize the service and initiate the challenge to put every health services across the country under a single umbrella. In the last decade, various socio-demographic factors forced to make a transitional shift towards non-communicable diseases which has significantly increases the number of health loss. City like Kolkata also faced the same challenges. Large archieve of unstructured health data furnish vital statistical measure on public health and valuable insight into different determinants of communicable & non-communicable diseases. The integration of various data sources along with analytical algorithm is used to assess risk factors and localized vulnerability to assist in developing effective prevention and control strategies for different diseases and to optimize allocation of limited public health resources. We propose an analytical framework based on multiple correlation, Gini Index and multiple Regression technique for analysing different causes related to NCD burden in Kolkata.