{"title":"日本对开放医学影像数据库的迫切需求:对全球卫生和人工智能发展的影响。","authors":"Daiju Ueda, Shannon Walston, Hirotaka Takita, Yasuhito Mitsuyama, Yukio Miki","doi":"10.1007/s11604-024-01716-y","DOIUrl":null,"url":null,"abstract":"<p><p>Japan leads OECD countries in medical imaging technology deployment but lacks open, large-scale medical imaging databases crucial for AI development. While Japan maintains extensive repositories, access restrictions limit their research utility, contrasting with open databases like the US Cancer Imaging Archive and UK Biobank. The 2018 Next Generation Medical Infrastructure Act attempted to address this through new data-sharing frameworks, but implementation has been limited by strict privacy regulations and institutional resistance. This data gap risks compromising AI system performance for Japanese patients and limits global medical AI advancement. The solution lies not in developing individual AI models, but in democratizing access to well-curated Japanese medical imaging data. By implementing privacy-preserving techniques and streamlining regulatory processes, Japan could enhance domestic healthcare outcomes while contributing to more robust global AI models, ultimately reclaiming its position as a leader in medical innovation.</p>","PeriodicalId":14691,"journal":{"name":"Japanese Journal of Radiology","volume":" ","pages":"537-541"},"PeriodicalIF":2.1000,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11953178/pdf/","citationCount":"0","resultStr":"{\"title\":\"The critical need for an open medical imaging database in Japan: implications for global health and AI development.\",\"authors\":\"Daiju Ueda, Shannon Walston, Hirotaka Takita, Yasuhito Mitsuyama, Yukio Miki\",\"doi\":\"10.1007/s11604-024-01716-y\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Japan leads OECD countries in medical imaging technology deployment but lacks open, large-scale medical imaging databases crucial for AI development. While Japan maintains extensive repositories, access restrictions limit their research utility, contrasting with open databases like the US Cancer Imaging Archive and UK Biobank. The 2018 Next Generation Medical Infrastructure Act attempted to address this through new data-sharing frameworks, but implementation has been limited by strict privacy regulations and institutional resistance. This data gap risks compromising AI system performance for Japanese patients and limits global medical AI advancement. The solution lies not in developing individual AI models, but in democratizing access to well-curated Japanese medical imaging data. By implementing privacy-preserving techniques and streamlining regulatory processes, Japan could enhance domestic healthcare outcomes while contributing to more robust global AI models, ultimately reclaiming its position as a leader in medical innovation.</p>\",\"PeriodicalId\":14691,\"journal\":{\"name\":\"Japanese Journal of Radiology\",\"volume\":\" \",\"pages\":\"537-541\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2025-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11953178/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Japanese Journal of Radiology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s11604-024-01716-y\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/12/13 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Japanese Journal of Radiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s11604-024-01716-y","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/12/13 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
The critical need for an open medical imaging database in Japan: implications for global health and AI development.
Japan leads OECD countries in medical imaging technology deployment but lacks open, large-scale medical imaging databases crucial for AI development. While Japan maintains extensive repositories, access restrictions limit their research utility, contrasting with open databases like the US Cancer Imaging Archive and UK Biobank. The 2018 Next Generation Medical Infrastructure Act attempted to address this through new data-sharing frameworks, but implementation has been limited by strict privacy regulations and institutional resistance. This data gap risks compromising AI system performance for Japanese patients and limits global medical AI advancement. The solution lies not in developing individual AI models, but in democratizing access to well-curated Japanese medical imaging data. By implementing privacy-preserving techniques and streamlining regulatory processes, Japan could enhance domestic healthcare outcomes while contributing to more robust global AI models, ultimately reclaiming its position as a leader in medical innovation.
期刊介绍:
Japanese Journal of Radiology is a peer-reviewed journal, officially published by the Japan Radiological Society. The main purpose of the journal is to provide a forum for the publication of papers documenting recent advances and new developments in the field of radiology in medicine and biology. The scope of Japanese Journal of Radiology encompasses but is not restricted to diagnostic radiology, interventional radiology, radiation oncology, nuclear medicine, radiation physics, and radiation biology. Additionally, the journal covers technical and industrial innovations. The journal welcomes original articles, technical notes, review articles, pictorial essays and letters to the editor. The journal also provides announcements from the boards and the committees of the society. Membership in the Japan Radiological Society is not a prerequisite for submission. Contributions are welcomed from all parts of the world.