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Predictive analysis in Gestational Diabetic Mellitus (GDM) using HCNN-LSTM/DPNN (Big Data)

机译:使用HCNN-LSTM / DPNN(大数据)在妊娠糖尿病MELLITUS(GDM)的预测分析

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The Statistical report from International Diabetes Federation (IDF), in 2020, 463 million people are increasingly affected by diabetes across the globe and particularly 88 million people in the Southeast Asia region. Of the 88 million people, 77 million people belong to India. IDF said India occupies the second highest place of children affected with type 1 diabetes after the United States. As per the World Health Organization (WHO), overall 2% of deaths that are occurred in India will be due to diabetes. According to IGT (Impaired Glucose Tolerance), 35% of sufferers will have Type 2 diabetes, so it can be strongly concluded that India is significantly requiring a healthcare emergency. This paper discusses the seriousness and impact of diabetes (Type1, Type2, and GDM). And also important to reveal and discuss the accuracy of the proposed methodology over the other existing methodologies. It is important to the early prediction using the HCNN-LSTM Algorithm using Big Data technology. According to the IDF report, the patients' records are huge volume, to manage and store all patients' records HDFS storage is required and it is under the big data technology.
机译:2020年,国际糖尿病联合会(IDF)的统计报告,4.63亿人越来越受到全球糖尿病的影响,尤其是东南亚地区的4800万人。在8800万人中,7700万人属于印度。 IDF表示,印度占据在美国后1型糖尿病影响的儿童的第二高。根据世界卫生组织(世卫组织),印度发生的总体2%的死亡将是由于糖尿病。根据IGT(葡萄糖耐量受损),35%的患者将有2型糖尿病,因此可以强烈得出明显需要医疗保健的紧急情况。本文讨论了糖尿病(Type1,Type2和GDM)的严重性和影响。同样重要的是揭示和讨论所提出的方法对其他现有方法的准确性。使用大数据技术使用HCNN-LSTM算法的早期预测是重要的。根据IDF报告,患者的记录是巨大的批量,管理和储存所有患者的记录HDFS储存是必需的,它是在大数据技术下。

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