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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...

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Autores principales: Aisu, Nao, Miyake, Masahiro, Takeshita, Kohei, Akiyama, Masato, Kawasaki, Ryo, Kashiwagi, Kenji, Sakamoto, Taiji, Oshika, Tetsuro, Tsujikawa, Akitaka
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9931274/
https://www.ncbi.nlm.nih.gov/pubmed/36812514
http://dx.doi.org/10.1371/journal.pdig.0000001
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author Aisu, Nao
Miyake, Masahiro
Takeshita, Kohei
Akiyama, Masato
Kawasaki, Ryo
Kashiwagi, Kenji
Sakamoto, Taiji
Oshika, Tetsuro
Tsujikawa, Akitaka
author_facet Aisu, Nao
Miyake, Masahiro
Takeshita, Kohei
Akiyama, Masato
Kawasaki, Ryo
Kashiwagi, Kenji
Sakamoto, Taiji
Oshika, Tetsuro
Tsujikawa, Akitaka
author_sort Aisu, Nao
collection PubMed
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.
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spelling pubmed-99312742023-02-16 Regulatory-approved deep learning/machine learning-based medical devices in Japan as of 2020: A systematic review Aisu, Nao Miyake, Masahiro Takeshita, Kohei Akiyama, Masato Kawasaki, Ryo Kashiwagi, Kenji Sakamoto, Taiji Oshika, Tetsuro Tsujikawa, Akitaka PLOS Digit Health Research Article 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. Public Library of Science 2022-01-18 /pmc/articles/PMC9931274/ /pubmed/36812514 http://dx.doi.org/10.1371/journal.pdig.0000001 Text en © 2022 Aisu et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Aisu, Nao
Miyake, Masahiro
Takeshita, Kohei
Akiyama, Masato
Kawasaki, Ryo
Kashiwagi, Kenji
Sakamoto, Taiji
Oshika, Tetsuro
Tsujikawa, Akitaka
Regulatory-approved deep learning/machine learning-based medical devices in Japan as of 2020: A systematic review
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
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9931274/
https://www.ncbi.nlm.nih.gov/pubmed/36812514
http://dx.doi.org/10.1371/journal.pdig.0000001
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