Diabetes Prediction using Different Machine Learning Techniques

Even though diabetes is a worldwide epidemic, there is no cure for it. Furthermore, Healthcare for people with diabetes costs a lot of money every year. As a result, the most critical consideration is the accuracy of the forecast and the selection of an appropriate methodology. Artificial Neural Networks (ANNs) and artificial intelligence systems are two examples of these techniques (ANN). As a result, artificial neural networks were employed in this study to determine whether a subject has diabetes. Furthermore, a neural network error function was also used as a criterion during training. After the neural network was trained, it was 99.6% accurate in predicting if a person had diabetes, with an average error of 0.01.