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±èÁöÇö ( Kim Jie-Hyun ) 
Yonsei University College of Medicine Department of Internal Medicine

Á¤Çö¼ö ( Chung Hyun-Soo ) 
Seoul National University College of Medicine Department of Internal Medicine
±èÇö¼ö ( Kim Hyun-Soo ) 
Yonsei University Wonju College of Medicine Department of Internal Medicine
±è¼ö¿µ ( Kim Su-Young ) 
Yonsei University Wonju College of Medicine Department of Internal Medicine
Â÷Àç¸í ( Cha Jae-Myung ) 
Kyung Hee University College of Medicine Department of Internal Medicine
ÀÌâ±Õ ( Lee Chang-Kyun ) 
Kyung Hee University College of Medicine Department of Internal Medicine
¹Úº´±Ô ( Park Byung-Kyu ) 
National Health Insurance Service Ilsan Hospital Division of Gastroenterology
¹Ú¼ÒÈñ ( Park So-Hee ) 
Yonsei University Graduate School of Public Health

Abstract


The Big Data Research Committee of the Korean Society of Gastroenterology conducted activities and researches with three goals. First, it provides the basis for proper and cost-effective treatment of digestive diseases in Korea. Second, it carries out population- level global research by establishing a system of big data analysis related to gastroenterology. Third, it provides the members of the Korean Society of Gastroenterology with the opportunity to plan and assess the public interest related to big data. The studies published by the committee members in this paper were carried out under these objectives, and the findings are believed to have achieved the public interest goals that may be helpful in the current medical and health policy. The construction of the big data infrastructure for digestive drugs is also underway, and we expect to see meaningful results pertaining to important digestive drugs. Research using public health medical big data, such as the National Health Insurance Corporation data base, should ultimately provide a basis for reflecting public messages and policies for the public. To this end, it is necessary for Korean researchers to lead efforts to lower the barriers and to approach relevant information and opportunities using big data research.

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Research; Big data; Gastroenterology

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