Our team has developed a rapid microfluidic paper-based chip detection system that utilizes smart networking technology to upload results to the cloud for management and analysis. The system establishes predictive models to generate personalized reports, providing doctors and patients with immediate and accurate assessments and recommendations, achieving the goal of home testing. Through this innovative system, we aim to provide better health management tools for chronic kidney disease patients.

Currently, there is a lack of systems that can simultaneously test blood and urine index and comprehensively manage and analyze, making it difficult for patients to understand their status. Our team has developed a system that uses AIoT to upload results to the cloud. By integrating generative AI and machine learning to build predictive models, it generates personalized reports, providing real-time, accurate recommendations. It supports remote diagnosis and monitoring of disease progression.

Our team has developed a system that integrates hardware and software technologies, including AI programs and a cloud database, to provide tracking of data and monitoring. The target market is CKD patients, with over 2.63 million in Taiwan and more than 850 million worldwide. The results can assist doctors in diagnosis. Compared to market products, our system improves accuracy, monitoring, and predictive precision. It can be commercialized through partnerships with technology transfer companies.