Multi-layered deep learning perceptron approach for health risk prediction

In today's world, due to the increase of medical data there is an interest in data preprocessing, classification and prediction of disease risks. Machine learning and Artificial Intelligence indicates that the predictive analysis becomes part of the medical activities especially in the domain of medical death prevention. The proposed work is focused on supervised learning methods and their capability to find hidden patterns in the real historical medical data. The objective is to predict future risk with a certain probability using Multi-layer perceptron (MLP) method. In the proposed work, MLP based on data classification technique is used for accurate classification and risk analysis of medical data. The proposed method is compared with traditional classification methods and the results show that the proposed method is better than the traditional methods.