Abstract: Artificial intelligence (AI)-powered audio analysis technology enables non-invasive and accurate detection of infectious diseases by identifying disease-induced changes in sound. At the technical level, convolutional neural networks represent the established mainstream algorithmic framework, demonstrating adaptability to a wide variety of detection tasks. At the application level,AI can develop automated analysis models by capturing multimodalsignals such as coughs and breath sounds. These models assist auscultation diagnosis and disease screening in medical institutions, and further enable the development of remote monitoring tools in community settings through the integration of mobile devices and cloud computing. Current challenges include limited availability of databases, insufficient interpretability and pathogen mutations. This technology is expected to be a highly effective approach for identification of infectious diseases through building high-quality databases and boosting cross-disciplinary collaboration.