A deep learning-based chest X-ray cardiovascular disease diagnosis assistant solution, developed by Asan Medical Center, won two main awards at Germany’s international design competition, the ‘iF Design Award’ 2024. The solution was honored in the categories of ‘Service Design’ and ‘User Experience (UX).’

This solution, developed as a Research-driven Hospital Development R&D Project, involved Professor Dong Hyun Yang of the Department of Radiology participating in research and development with support from the Innovation Design Center for UX/UI planning and design.

Previously, the identification of cardiovascular borders and the measurement of their lengths and angles relied on manual methods, leading to deviations and time consumption influenced by individual skill levels. With the integration of deep learning technology, this solution automates the analysis of cardiovascular borders and presents visualized results. Consequently, it is poised to significantly reduce examination time while facilitating objective diagnosis and prediction.