On the 13th, ASUS unveiled its new Ultrasound AI Platform, designed to popularize cloud-based AI training and edge inference applications. This platform aims to assist physicians, healthcare institutions, research organizations, and academic institutions in accelerating the development of personalized AI models for ultrasound, providing novel insights and clinical validation tools for medical research.

The standout feature of the ASUS Ultrasound AI Platform is its no-code AI development system. With an intuitive graphical interface, healthcare professionals can develop personalized ultrasound AI models through a straightforward three-step process: data collection and annotation, cloud-based model training, and weight deployment with edge inference. This approach allows users to create AI models without any programming knowledge.

Professor Po-Hsiang Tsui of Chang Gung University, who participated in the product development, provided an example involving the use of ultrasound to examine fatty liver. By importing the images into the platform to generate an AI model, the progression of fatty liver in patients with the same condition can be quantified. This enables efficient tracking of liver disease prevention or metabolic syndrome management without the need for manual interpretation or learning to code. The Ultrasound AI Platform significantly improves speed and efficiency.

Chuan-Te Chang, ASUS Global Vice President and Co-General Manager of the Smart IoT Business Group, highlighted that the newly launched Ultrasound AI Platform significantly lowers the programming barrier for physicians and researchers in clinical studies. It eliminates the tedious process of manually interpreting ultrasound images. Chang emphasized ASUS’s commitment to advancing smart healthcare by integrating computing power, cloud services, and information and communication technology, continuing to drive innovation and application outcomes.

Resource (mandarin): 無程式碼開發，華碩發表個人化超音波 AI 模型搶攻智慧醫療