¹ÚÂù¿ì(Park Chan-Woo) - Sungkyunkwan University School of Medicine Samsung Medical Center Department of Orthopedic Surgery
¼¼º¿í(Seo Sung-Wook) - Sungkyunkwan University School of Medicine Samsung Medical Center Department of Orthopedic Surgery
°³ëÀ»(Kang No-Eul) - Sungkyunkwan University School of Medicine Samsung Medical Center Department of Medicine
°í¹ü¼®(Ko Beom-Seok) - University of Ulsan College of Medicine Asan Medical Center Department of Surgery
ÃÖº´¿í(Choi Byung-Wook) - Yonsei University College of Medicine Severance Hospital Department of Radiology
¹Úâ¹Î(Park Chang-Min) - Seoul National University College of Medicine Department of Radiology
À嵿°æ(Chang Dong-Kyung) - Sungkyunkwan University School of Medicine Samsung Medical Center Department of Medicine
±èÈÖ¿õ(Kim Hwi-Uoung) - Yonsei University College of Medicine Severance Hospital Department of Radiology
±èÇöö(Kim Hyun-Chul) - Korea Health Industry Development Institute Department of R&D Planning
ÀÌÇö³ª(Lee Hyun-Na) - Asan Medical Center Asan Institute for Life Sciences Health Innovation Big Data Center
ÀåÁøÈñ(Jang Jin-Hee) - Catholic University College of Medicine Seoul St. Mary¡¯s Hospital Department of Radiology
¿¹Á¾Ã¶(Ye Jong-Chul) - Korea Advanced Institute of Science and Technology Department of Bio and Brain Engineering
ÀüÁ¾È«(Jeon Jong-Hong) - Electronics and Telecommunications Research Institute Protocol Engineering Center
¼Áعü(Seo Joon-Beom) - University of Ulsan College of Medicine Asan Medical Center Department of Radiology
±è±¤ÁØ(Kim Kwang-Joon) - Yonsei University College of Medicine Severance Hospital Department of Internal Medicine
Á¤±Ôȯ(Jung Kyu-Hwan) - VUNO Inc.
±è³²±¹(Kim Nam-Kug) - University of Ulsan College of Medicine Asan Medical Center Department of Convergence Medicine
¹é½Â¿í(Paek Seung-Wook) - Lunit Inc.
½Å¼ö¿ë(Shin Soo-Yong) - Sungkyunkwan University School of Medicine Samsung Medical Center Big Data Research Center
À¯¼Ò¿µ(Yoo So-Young) - Asan Medical Center Asan Institute for Life Sciences Health Innovation Big Data Center
ÃÖÀ±¼·(Choi Yoon-Sup) - Digital Healthcare Partners
±è¿µÁØ(Kim Young-Jun) - Korea Institute of Science and Technology Center for Bionics
À±ÇüÁø(Yoon Hyung-Jin) - Seoul National University College of Medicine Department of Biomedical Engineering
Abstract
In recent years, artificial intelligence (AI) technologies have greatly advanced and become a reality in many areas of our daily lives. In the health care field, numerous efforts are being made to implement the AI technology for practical medical treatments. With the rapid developments in machine learning algorithms and improvements in hardware performances, the AI technology is expected to play an important role in effectively analyzing and utilizing extensive amounts of health and medical data. However, the AI technology has various unique characteristics that are different from the existing health care technologies. Subsequently, there are a number of areas that need to be supplemented within the current health care system for the AI to be utilized more effectively and frequently in health care. In addition, the number of medical practitioners and public that accept AI in the health care is still low; moreover, there are various concerns regarding the safety and reliability of AI technology implementations. Therefore, this paper aims to introduce the current research and application status of AI technology in health care and discuss the issues that need to be resolved.
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Artificial Intelligence, Machine Learning, Health Care, Application, Issue
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À¯È¿¼º°á°ú(Recomendation)
The currently available AI-based health care technologies have shown outstanding results in accurately diagnosing and classifying patient conditions and predicting the course of diseases by using the accumulated medical data.