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.

中文翻译：

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多层深度学习感知器方法用于健康风险预测

在当今世界，由于医学数据的增加，人们对数据预处理，疾病风险的分类和预测产生了兴趣。机器学习和人工智能表明，预测分析已成为医疗活动的一部分，尤其是在医疗死亡预防领域。拟议的工作集中在监督学习方法及其在真实历史医学数据中发现隐藏模式的能力。目的是使用多层感知器（MLP）方法以一定概率预测未来风险。在本文的工作中，基于数据分类技术的MLP用于医学数据的准确分类和风险分析。