The field of Artificial Intelligence & Robotics in Life Science has undergone significant modernization, leading to a substantial increase in output. One of the most effective AI techniques in this sector is Vocal Biomarkers, which utilizes deep learning algorithms to detect various diseases related to the heart, lungs, and neural system such as Cardiometabolic and Cardiovascular disease, Parkinson's disease, Alzheimer’s disease, Multiple Sclerosis, and more in their early stages by analyzing multilayered neural networks from a vast amount of data based on voice pitch, verbal vocalization, and non-verbal vocalization. It is important to note that disorders can have a significant impact on both immune and vocal health. This presentation provides an overview of diseases detected by vocal biomarkers, the type of speech recorder used, its technique and working process, as well as its potential for more effective use in the future within the healthcare sector.