Human Sound Detection for Multiple Disease Classification Using CNN

Coughing is an everyday sign of various respiratory infections. The sound and type of coughing are significant features to consider while identifying a condition. Respiratory infections are a global health risk and economic burden, especially in nations with limited treatment options. This study observes the current technology proposing multiple disease classification used to control the impact of respiratory disorders. Artificial intelligence (AI)-based models have been implemented in the everyday life to identify various diseases using human-generated sounds for example voice, dry cough, and breath. The convolutional neural network (CNN) is utilized to tackle numerous real-world problems using AI devices. We suggested and constructed a modified CNN to automatically diagnose disease using human respiratory noises like voice, dry cough, and breath. This paper discusses the utmost current difficulties, answers, and chances in respiratory disease recognition and analysis, allowing physicians and investigators to build new strategies that will provide greater accuracy and performance than prior models.