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In today’s scenario, Diabetes is the most common disease for human beings. In diabetes, the sugar level is increased due to the genetic problem or due to tension taken by human beings. The main aim of this study is to predict the diabetes by using Machine learning techniques. In this paper we collect the data which is affected be diabetes using the characteristics defined by American Diabetes Association (ADA) criteria. We evaluate the real-world data by using machine learning techniques. In this, we obtain the precision value is less than 5.7, then the person is non-diabetic and if the precision value is greater than or equal to 6.5, then the person is diabetic. This precision value is achieved with the Glycosylated Hemoglobin test.

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Type 2 Diabetes Prediction Using Machine Learning: A Game-Changer for Healthcare

  • 会议论文

  • 发表日期：

    2025年

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  • Sadhana Singh,
  • Priyanka Sharma,
  • Pragya Pandey

摘要

In today’s scenario, Diabetes is the most common disease for human beings. In diabetes, the sugar level is increased due to the genetic problem or due to tension taken by human beings. The main aim of this study is to predict the diabetes by using Machine learning techniques. In this paper we collect the data which is affected be diabetes using the characteristics defined by American Diabetes Association (ADA) criteria. We evaluate the real-world data by using machine learning techniques. In this, we obtain the precision value is less than 5.7, then the person is non-diabetic and if the precision value is greater than or equal to 6.5, then the person is diabetic. This precision value is achieved with the Glycosylated Hemoglobin test.