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A Multilingual Decision Support System for early detection of Diabetes using Machine Learning approach: Case study for Rural Indian people

机译:利用机器学习方法早期检测糖尿病的多语言决策支持系统:乡村印度人案例研究

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More than 77 million people in India are influenced by diabetes mellitus and a significant number of them are under risk with specific complications, for instance cardiovascular failure, stroke, nerve infection, etc., The prevalence ratio of diabetes is high in urban areas due to the migration of rural people and industrialization. While considering diabetes in prosperous urban, it has become a grave anxiety among rural people also. Early diagnosis and proper therapeutic management may reduce the expenditure and mortality rate. however, the cost of early diagnosis and laboratory testing is very high. To provide a user-friendly and cost-effective system, this paper proposes a multilingual decision support system by integrating the best predictive model (among various machine learning algorithms) and clinical decision support system. The proposed system provides a user interface to assess diabetes by themselves or with a nursing assistant available in primary health centre.
机译:印度超过7700万人受到糖尿病的影响,其中大量有很多人受到特异性并发症的风险,例如心血管失败,中风,神经感染等,糖尿病的患病率在城市地区患有高度的城市地区农村人民与产业化的迁移。在考虑繁荣城市的糖尿病的同时,它也成为农村人民的严重焦虑。早期诊断和适当的治疗管理可能会降低支出和死亡率。然而,早期诊断和实验室测试的成本非常高。为了提供用户友好且经济高效的系统,本文通过集成最佳预测模型(各种机器学习算法)和临床决策支持系统来提出多语言决策支持系统。所提出的系统提供了用户界面,用于自行评估糖尿病或在主要保健中心提供的护理助理。

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