Updated Model Deep Learning Methods for Classification of Respiratory Diseases Using Different Medical Imaging and Cough Sounds

Introduction: The respiratory disease has caused irreparable damage to the world. In order to prevent the spread of pathogenic, it is necessary to identify infected people for quarantine and treatment. The use of artificial intelligence and deep learning approaches can lead to prevention and reduction of treatment costs. The purpose of this study is to create deep learning models in order to diagnose people with the respiratory disease through the sound of coughing. Background: This study aimed to propose an automatic prediction of respiratory disease like Cough using cough sound based on deep learning models algorithms. Result: With the data here it is collected (about 254 people) in different networks, we have reached acceptable accuracies. Conclusions: To the best of our knowledge, this study is the first to test the potential of deep learning methods for chronic cough investigation, which also shows a great advantage over existing algorithms for patient data clustering.