MEDICAL IP verifies ‘AI body composition analysis technology’ through renowned international academic journals

▶ Through a paper published in 'The American Journal of Clinical Nutrition', it has been confirmed that DeepCatch is capable of 'predicting diseases,' such as sarcopenia and metabolic syndrome.

▶ The goal is to establish a medical process and guideline that presents the disease risk as soon as CT is taken

<2021-07-27> Medical IP's self-developed AI body composition analysis technology is realizing 'disease prediction artificial intelligence'.
MEDICAL IP confirmed that the AI body composition analysis solution 'DeepCatch' can be used to predict metabolic diseases and sarcopenia through a paper published in the international scientific journal, 'The American Journal of Clinical Nutrition'.

According to the paper, it was confirmed that, when DeepCatch is used, it is possible to accurately segment body components, such as muscle, fat, and bone density, on a CT image, as well as assist in the evaluation of sarcopenia and metabolic diseases through numerical information for each area. This study was led by Professor Soon-ho Yoon of the Department of Radiology at Seoul National University Hospital, and Professor Lee Yu-mi and Hong Nam-gi of the Department of Endocrinology at Severance Hospital. The CT data held by each hospital was analyzed with DeepCatch, and the accuracy of the result was verified with data from two domestic institutions and one French institution.

The research team said, “Sarcopenia is a representative disease of the elderly that must be dealt with in an aging society, but it has been underestimated due to the limitation that a separate detailed examination is required. It has been confirmed that the disease can be predicted by three-dimensional measurement and AI technology.”