On the first day of the conference, Professor Nam-ki Hong from the Department of Endocrinology at Yonsei University Severance Hospital, as the first presenter at ‘AI Stage’ session, drew attention by announcing the clinical research results using MEDICAL IP's automatic medical image-based body composition analysis technology.
According to clinical results, DeepCatch's automatic AI body composition analysis technology can establish standard indicators of body composition for healthy people through CT big data.
Based on the results, it has been emphasized that DeepCatch can be used to predict and respond to risks, such as metabolic syndrome, sarcopenia, and osteoporosis.
Professor Hong Nam-ki said, “Changes in body composition, such as bones, muscles, and visceral fat, are factors that can determine chronic diseases related to aging. CT is data that can obtain quantitative information about body composition, and DeepCatch's AI technology, which analyzes body composition and calculates numerical information from CT, is useful for discovering body composition biomarkers and determining the possibility of multiple diseases including metabolic diseases. It will play a key role.”
Based on this differentiated technology, the demand for DeepCatch from medical staff and researchers who conduct CT analysis research is continuously increasing. With this KCR 2021 as an opportunity, more joint research and discussions on technology supply are expected.
