Korea University Ansan Hospital Diabetes Prediction Software Acquires License to Manufacture Medical Devices
Jun 16, 2025
A diabetes risk analysis software (hereinafter, JDA-01K) developed by a research team led by Professor Nan-hee Kim of the Department of Endocrinology at Korea University Ansan Hospital (Professors Nan-hee Kim, So-young Park, Medical Life Research Center Kim Min-hee and Jae-young Kim) recently obtained permission to manufacture medical devices from the Ministry of Food and Drug Safety (hereinafter, Ministry of Food and Drug Safety). JDA-01K is the first approved case of the 'Diabetes Risk Assessment Software' item newly established by the Ministry of Food and Drug Safety in February last year.
JDA-01K is a software that can predict the risk of diabetes based on clinical data and genetic information by applying machine learning and deep learning technologies. Earlier, Professor Kim Nan-hee's team completed domestic patent registration with the technology.
Diabetes is difficult to cure once it occurs and can cause various complications, so prevention before the outbreak is of paramount importance. In particular, a system is needed to select and preemptively manage high-risk groups early to reduce the economic burden caused by diabetes, such as medical expenses.
In fact, according to the Korea Centers for Disease Control and Prevention's official journal Health and Disease released last year, the number of diabetic patients as of last year was 3.69 million and the annual medical expenses were 3.4 trillion won, with the number of patients increasing by about 1.47 million and medical expenses increasing by more than 2 trillion won over the past decade.
The software can be used to assist medical professionals in diagnostic decisions by displaying the risk of developing diabetes based on clinical data and genetic information. When a medical professional enters clinical data such as the user's body information and blood test results into the system, the risk and major risk factors of diabetes can be identified based on the results of integrated analysis with genetic information, and customized prevention measures can be derived.
Previously, the research team conducted retrospective clinical trials using data from 2,556 adults over the age of 40 who underwent medical checkups and genetic tests from 2004 to 2016 and demonstrated the safety and effectiveness of the system.
Professor Nanhee Kim said, "This acquisition of the Ministry of Food and Drug Safety's approval means that it has been recognized for its reliability and applicability as an official medical device"In the future, we plan to expand the prediction to other chronic diseases such as high blood pressure and metabolic syndrome and conduct further research with the aim of developing personal health care services through mobile app linkage."
JDA-01K is a software that can predict the risk of diabetes based on clinical data and genetic information by applying machine learning and deep learning technologies. Earlier, Professor Kim Nan-hee's team completed domestic patent registration with the technology.
Diabetes is difficult to cure once it occurs and can cause various complications, so prevention before the outbreak is of paramount importance. In particular, a system is needed to select and preemptively manage high-risk groups early to reduce the economic burden caused by diabetes, such as medical expenses.
In fact, according to the Korea Centers for Disease Control and Prevention's official journal Health and Disease released last year, the number of diabetic patients as of last year was 3.69 million and the annual medical expenses were 3.4 trillion won, with the number of patients increasing by about 1.47 million and medical expenses increasing by more than 2 trillion won over the past decade.
The software can be used to assist medical professionals in diagnostic decisions by displaying the risk of developing diabetes based on clinical data and genetic information. When a medical professional enters clinical data such as the user's body information and blood test results into the system, the risk and major risk factors of diabetes can be identified based on the results of integrated analysis with genetic information, and customized prevention measures can be derived.
Previously, the research team conducted retrospective clinical trials using data from 2,556 adults over the age of 40 who underwent medical checkups and genetic tests from 2004 to 2016 and demonstrated the safety and effectiveness of the system.
Professor Nanhee Kim said, "This acquisition of the Ministry of Food and Drug Safety's approval means that it has been recognized for its reliability and applicability as an official medical device"In the future, we plan to expand the prediction to other chronic diseases such as high blood pressure and metabolic syndrome and conduct further research with the aim of developing personal health care services through mobile app linkage."
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This article was translated by Naver AI translator.
