Using Neural Networks to Predict Diabetes Diagnosis through Backpropagation Algorithm

Abstract

Diabetes is a chronic disease caused by the body's inability to produce or effectively use insulin. This condition can lead to various serious complications. The backpropagation algorithm is one of the models found in Artificial Neural Networks (ANN) that employs supervised learning. This algorithm is often used to solve complex problems due to its training through learning methods. This study aims to develop an ANN model using the backpropagation algorithm to predict diabetes based on existing symptoms. By utilizing patients' medical records, this model is expected to provide accurate predictions regarding diabetes diagnosis