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Diabetes Prediction using Machine Learning Algorithms

机译:使用机器学习算法预测糖尿病预测

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Diabetes Mellitus is among critical diseases and lots of people are suffering from this disease. Age, obesity, lack of exercise, hereditary diabetes, living style, bad diet, high blood pressure, etc. can cause Diabetes Mellitus. People having diabetes have high risk of diseases like heart disease, kidney disease, stroke, eye problem, nerve damage, etc. Current practice in hospital is to collect required information for diabetes diagnosis through various tests and appropriate treatment is provided based on diagnosis. Big Data Analytics plays an significant role in healthcare industries. Healthcare industries have large volume databases. Using big data analytics one can study huge datasets and find hidden information, hidden patterns to discover knowledge from the data and predict outcomes accordingly. In existing method, the classification and prediction accuracy is not so high. In this paper, we have proposed a diabetes prediction model for better classification of diabetes which includes few external factors responsible for diabetes along with regular factors like Glucose, BMI, Age, Insulin, etc. Classification accuracy is boosted with new dataset compared to existing dataset. Further with imposed a pipeline model for diabetes prediction intended towards improving the accuracy of classification.
机译:糖尿病是患有这种疾病的关键疾病和许多人。年龄,肥胖,运动缺乏,遗传性糖尿病,生活方式,饮食不良,高血压等都会导致糖尿病。患有糖尿病的人具有高风险的疾病,肾脏疾病,中风,眼问题,神经损伤等。目前在医院的实践是通过各种测试收集糖尿病诊断所需的信息,并根据诊断提供适当的治疗。大数据分析在医疗保健行业中发挥着重要作用。医疗行业有大量数据库。使用大数据分析可以研究庞大的数据集并查找隐藏的信息,隐藏的模式,以发现来自数据的知识并相应地预测结果。在现有方法中,分类和预测精度不是那么高。在本文中,我们提出了一种糖尿病预测模型,用于更好地分类糖尿病,包括少数对糖尿病负责的外部因素以及葡萄糖,BMI,年龄,胰岛素等的常规因素。与现有数据集相比,分类准确性提升了新的数据集。此外,对于旨在提高分类准确性的糖尿病预测的管道模型。

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