A Special Multivariate Polynomial Model for Diabetes Prediction and Analysis

Abstract

Diabetes is one of the most common diseases worldwide. High level of blood sugar in diabetes patients can harm a large number of the body's system. Early prediction of diabetes can prevent or delay the disease. Various machine learning methods are used to predict diabetes in the past. Researchers usually aim for higher accuracy, the models used become more and more complex and their decision-making process is extremely difficult understood by users. However, explainability of a model is also critical to prediction task in medicine. A model which can enable users to easily understand its decision-making logic while maintaining good accuracy is more likely to be trusted by users. Therefore, we propose a special multivariate polynomial model to predict diabetes. This model has ability to show the relationship between each medical factor and diabetes with some polynomial curves, and the product of these curves and a specific constant is the decision-making process of the model. The experiment results show that our model also has a good accuracy compare with some other methods.