Regulatory-approved deep learning/machine learning-based medical devices in Japan as of 2020: A systematic review.
Machine learning (ML) and deep learning (DL) are changing the world and reshaping the medical field. Thus, we conducted a systematic review to determine the status of regulatory-approved ML/DL-based medical devices in Japan, a leading stakeholder in international regulatory harmonization. Informatio...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2022-01-01
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| Series: | PLOS Digital Health |
| Online Access: | https://doi.org/10.1371/journal.pdig.0000001 |
| _version_ | 1797695575994400768 |
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| author | Nao Aisu Masahiro Miyake Kohei Takeshita Masato Akiyama Ryo Kawasaki Kenji Kashiwagi Taiji Sakamoto Tetsuro Oshika Akitaka Tsujikawa |
| author_facet | Nao Aisu Masahiro Miyake Kohei Takeshita Masato Akiyama Ryo Kawasaki Kenji Kashiwagi Taiji Sakamoto Tetsuro Oshika Akitaka Tsujikawa |
| author_sort | Nao Aisu |
| collection | DOAJ |
| description | Machine learning (ML) and deep learning (DL) are changing the world and reshaping the medical field. Thus, we conducted a systematic review to determine the status of regulatory-approved ML/DL-based medical devices in Japan, a leading stakeholder in international regulatory harmonization. Information about the medical devices were obtained from the Japan Association for the Advancement of Medical Equipment search service. The usage of ML/DL methodology in the medical devices was confirmed using public announcements or by contacting the marketing authorization holders via e-mail when the public announcements were insufficient for confirmation. Among the 114,150 medical devices found, 11 were regulatory-approved ML/DL-based Software as a Medical Device, with 6 products (54.5%) related to radiology and 5 products (45.5%) related to gastroenterology. The domestic ML/DL-based Software as a Medical Device were mostly related to health check-ups, which are common in Japan. Our review can help understanding the global overview that can foster international competitiveness and further tailored advancements. |
| first_indexed | 2024-03-12T03:14:16Z |
| format | Article |
| id | doaj.art-8847a82f42fb48cd91a2d50b97e69512 |
| institution | Directory Open Access Journal |
| issn | 2767-3170 |
| language | English |
| last_indexed | 2024-03-12T03:14:16Z |
| publishDate | 2022-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLOS Digital Health |
| spelling | doaj.art-8847a82f42fb48cd91a2d50b97e695122023-09-03T14:14:29ZengPublic Library of Science (PLoS)PLOS Digital Health2767-31702022-01-0111e000000110.1371/journal.pdig.0000001Regulatory-approved deep learning/machine learning-based medical devices in Japan as of 2020: A systematic review.Nao AisuMasahiro MiyakeKohei TakeshitaMasato AkiyamaRyo KawasakiKenji KashiwagiTaiji SakamotoTetsuro OshikaAkitaka TsujikawaMachine learning (ML) and deep learning (DL) are changing the world and reshaping the medical field. Thus, we conducted a systematic review to determine the status of regulatory-approved ML/DL-based medical devices in Japan, a leading stakeholder in international regulatory harmonization. Information about the medical devices were obtained from the Japan Association for the Advancement of Medical Equipment search service. The usage of ML/DL methodology in the medical devices was confirmed using public announcements or by contacting the marketing authorization holders via e-mail when the public announcements were insufficient for confirmation. Among the 114,150 medical devices found, 11 were regulatory-approved ML/DL-based Software as a Medical Device, with 6 products (54.5%) related to radiology and 5 products (45.5%) related to gastroenterology. The domestic ML/DL-based Software as a Medical Device were mostly related to health check-ups, which are common in Japan. Our review can help understanding the global overview that can foster international competitiveness and further tailored advancements.https://doi.org/10.1371/journal.pdig.0000001 |
| spellingShingle | Nao Aisu Masahiro Miyake Kohei Takeshita Masato Akiyama Ryo Kawasaki Kenji Kashiwagi Taiji Sakamoto Tetsuro Oshika Akitaka Tsujikawa Regulatory-approved deep learning/machine learning-based medical devices in Japan as of 2020: A systematic review. PLOS Digital Health |
| title | Regulatory-approved deep learning/machine learning-based medical devices in Japan as of 2020: A systematic review. |
| title_full | Regulatory-approved deep learning/machine learning-based medical devices in Japan as of 2020: A systematic review. |
| title_fullStr | Regulatory-approved deep learning/machine learning-based medical devices in Japan as of 2020: A systematic review. |
| title_full_unstemmed | Regulatory-approved deep learning/machine learning-based medical devices in Japan as of 2020: A systematic review. |
| title_short | Regulatory-approved deep learning/machine learning-based medical devices in Japan as of 2020: A systematic review. |
| title_sort | regulatory approved deep learning machine learning based medical devices in japan as of 2020 a systematic review |
| url | https://doi.org/10.1371/journal.pdig.0000001 |
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