Predicting Diabetes using Machine Learning

Predicting Diabetes using Machine Learning

People get diabetes for a variety of reasons. Genetics can play a role in the development of diabetes, but lifestyle factors are also significant contributors. A diet high in processed foods and added sugars, lack of physical activity, obesity, and smoking can increase one’s risk of developing type 2 diabetes.

Having data about a person’s lifestyle can be incredibly useful in predicting the development of diabetes in the future. Research has repeatedly shown that certain lifestyle factors, such as low physical activity levels and poor dietary habits, are strongly associated with an increased risk of developing diabetes.

By collecting information on these and other crucial elements of an individual’s lifestyle, healthcare professionals can gain valuable insights into their overall health and potential risk for diabetes. With this knowledge, they can work with patients to develop targeted interventions and strategies to help mitigate their risk factors and prevent the onset of the disease.

In this post, I analyzed data from 100,000 patients’ test results and surveys and tried to predict their risk of getting diabetes. And I was able to build a model with 97% accuracy!


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