Cerebro-vascular and heart diseases have together ranked 4th and 5th place in the 2022 top ten leading causes of death in Hong Kong, taking up more than 15% of the total in an unceasing trend. While conventional carotid ultrasound imaging is nothing short of comprehensive, it is highly operator-dependent and is worsened by the shortage of medical staff in Hong Kong. The seemingly long queue for the expensive health screenings has put the high-risk groups, including but not limited to the elderly, in a vulnerable position as they can hardly perform regular and frequent check-ups. In light of this, our team is determined to research a solution that is conducive to the preventive healthcare of strokes and cardiovascular diseases through one of the newly proposed devices: PyrocksTM Tag Lite. This study aims to investigate an approach for developing a robust deep learning model for analysing ultrasound images and incorporate the model into our established prototype to perform intima-media thickness measurement and risk assessment. Main points that the clinical trial can assist in solving the existing problem: The acquisition procedures are non-invasive, painless, and safe for the participants. Clinical trials \& test data will assist in testing and training our neural network model.