KST-2023

Abstract

With the development of AI technology, AI is being introduced in many areas such as drug development and imaging diagnosis. However, the reality is that there are far more areas that have not yet been combined compared to the medical area where AI is being combined already. These differences appear depending on how prepared high-quality big data that AI can utilize is. In addition, 'high-quality big data that AI can utilize' depends on 'how well the medical practice is quantitatively defined and the measurement technology is standard'. In order to solve these problems, it is necessary to redefine the medical measurement parameters used in diagnosis so that they can be changed into digitized measurement values and to standardize devices that can measure them. When these works are done, we can make medical AI and also can implement AI-Ready Data Practices to Promote Equitable, Machine Readable, and Well-Defined clinical Big Data

Biography

Dr. Sanghun Lee is a Principal Researcher at KIOM in Korea and a professor at the University of Science and Technology. After majoring in Korean Traditional Medicine and working as a clinician and university research professor, he joined the Institute of Oriental Medicine in 2009 as a researcher. His primary research areas are standardization and scientificization of Traditional medicine devices, biomarkers, and medical information. He is a member of the Young Korean Academy of Science and Technology, and education director at the Society for Meridian and Acupoint. Currently, he is leading the research project of 'Establishment of AI Korean medicine doctor development infrastucture' in KIOM.and gobal standard development as a Project leader in International Organization for Standardization Technical Committee 249 (Traditional Chinese Medicine) about Traditional Medicine devices