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learning algorithms. In this paper, we review the classification algorithmsused in the health care system (chronic diseases) and present the neuralnetwork-based Ensemble learning method. We briefly describe the commonly usedalgorithms and describe their critical properties. Materials and Methods: Inthis study, modern classification algorithms used in healthcare, examine theprinciples of these methods and guidelines, and to accurately diagnose andpredict chronic diseases, superior machine learning algorithms with the neuralnetwork-based ensemble learning Is used. To do this, we use experimental data,real data on chronic patients (diabetes, heart, cancer) available on the UCIsite. Results: We found that group algorithms designed to diagnose chronicdiseases can be more effective than baseline algorithms. It also identifiesseveral challenges to further advancing the classification of machine learningin the diagnosis of chronic diseases. Conclusion: The results show the highperformance of the neural network-based Ensemble learning approach for thediagnosis and prediction of chronic diseases, which in this study reached 98.5,99, and 100% accuracy, respectively.

Deep Neural Network Based Ensemble learning Algorithms for the healthcare system (diagnosis of chronic diseases)