加尔各答非传染性疾病影响的大数据分析框架

Supratim Bhattacharya, Jayanta Poray, Priyanka Debnath
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引用次数: 0

摘要

考虑到城市化的逐步推进,城市卫生已成为印度当前十年最具挑战性的任务之一。在国家一级开始了一项详尽和协调的工作,以便使服务标准化,并发起挑战,将全国所有保健服务置于一个统一的保护伞下。在过去十年中,各种社会人口因素迫使过渡转向非传染性疾病,这大大增加了健康损失的人数。加尔各答等城市也面临着同样的挑战。庞大的非结构化卫生数据档案提供了关于公共卫生的重要统计措施,并对传染性和非传染性疾病的不同决定因素提供了宝贵的见解。将各种数据源与分析算法结合起来,用于评估风险因素和局部脆弱性,以协助制定针对不同疾病的有效预防和控制战略,并优化有限的公共卫生资源的分配。我们提出了一个基于多重相关、基尼指数和多元回归技术的分析框架,用于分析与加尔各答非传染性疾病负担相关的不同原因。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
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