한의학과 인공지능의 융합: 특허 동향 분석과 향후 방향
The Fusion of Korean Medicine and Artificial Intelligence : Patent Trend Analysis and Future Directions
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Objectives : The development of artificial intelligence (AI) has driven changes across various sectors, including medicine. This study examines patent trends in the integration of Korean medicine (KM) and AI, an area previously unexplored. Methods : Patents published and registered until February 2024 were retrieved from KIPRIS, a patent information database. Search terms included ‘han-ui-hak’, ‘hanbang’, ‘artificial intelligence’, ‘deep learning’, ‘machine learning’, and ‘AI’. A total of 153 KM-AI patents were identified and categorized by application year, patentee, patent content (prevention, diagnosis, treatment, etc.), AI technology (rule-based, learning, cognitive, inference), and data type (structured, video, voice, natural language, signal, composite). Results : A total of 153 patents related to the combination of KM and Al were selected and analyzed. Patent applications began with one in 2008 and peaked at 23 in 2021. The Korea Institute of Oriental Medicine held the majority with 118 (77.12%), while other entities filed 33 (22.88%). Patent contents were primarily for diagnosis (53.59%), followed by treatment (11.76%) and prevention(8.50%), with 34 patents (22.22%) covering multiple areas. Most AI technologies used were rule-based (75.16%), followed by learning (13.07%), inference (10.46%), and cognitive (2%). Data types included structured (25.49%), video (33.33%), voice (3.92%), natural language (6.54%), signal (18.95%), and composite (11.76%). Conclusion : KM-AI integration is progressing actively, indicating KM’s potential to evolve with modern trends. However, it is thought that more multidisciplinary research between the KM community and other academic disciplines should be encouraged.
Abstract
Objectives : The development of artificial intelligence (AI) has driven changes across various sectors, including medicine. This study examines patent trends in the integration of Korean medicine (KM) and AI, an area previously unexplored. Methods : Patents published and registered until February 2024 were retrieved from KIPRIS, a patent information database. Search terms included ‘han-ui-hak’, ‘hanbang’, ‘artificial intelligence’, ‘deep learning’, ‘machine learning’, and ‘AI’. A total of 153 KM-AI patents were identified and categorized by application year, patentee, patent content (prevention, diagnosis, treatment, etc.), AI technology (rule-based, learning, cognitive, inference), and data type (structured, video, voice, natural language, signal, composite). Results : A total of 153 patents related to the combination of KM and Al were selected and analyzed. Patent applications began with one in 2008 and peaked at 23 in 2021. The Korea Institute of Oriental Medicine held the majority with 118 (77.12%), while other entities filed 33 (22.88%). Patent contents were primarily for diagnosis (53.59%), followed by treatment (11.76%) and prevention(8.50%), with 34 patents (22.22%) covering multiple areas. Most AI technologies used were rule-based (75.16%), followed by learning (13.07%), inference (10.46%), and cognitive (2%). Data types included structured (25.49%), video (33.33%), voice (3.92%), natural language (6.54%), signal (18.95%), and composite (11.76%). Conclusion : KM-AI integration is progressing actively, indicating KM’s potential to evolve with modern trends. However, it is thought that more multidisciplinary research between the KM community and other academic disciplines should be encouraged.
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