Combining machine learning and nanopore construction creates an artificial intelligence nanopore for coronavirus detection
Rapid, accurate and specific point-of-care diagnostics can help manage and contain fast-spreading infections. Here, the authors present a nanopore-based system that uses artificial intelligence to discriminate between four coronaviruses in saliva, with little need for sample pre-processing.
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Nature Portfolio
2021
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oai:doaj.org-article:7cfcb758d04548a9925462a3e647155b2021-12-02T17:40:27ZCombining machine learning and nanopore construction creates an artificial intelligence nanopore for coronavirus detection10.1038/s41467-021-24001-22041-1723https://doaj.org/article/7cfcb758d04548a9925462a3e647155b2021-06-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-24001-2https://doaj.org/toc/2041-1723Rapid, accurate and specific point-of-care diagnostics can help manage and contain fast-spreading infections. Here, the authors present a nanopore-based system that uses artificial intelligence to discriminate between four coronaviruses in saliva, with little need for sample pre-processing.Masateru TaniguchiShohei MinamiChikako OnoRina HamajimaAyumi MorimuraShigeto HamaguchiYukihiro AkedaYuta KanaiTakeshi KobayashiWataru KamitaniYutaka TeradaKoichiro SuzukiNobuaki HatoriYoshiaki YamagishiNobuei WashizuHiroyasu TakeiOsamu SakamotoNorihiko NaonoKenji TatematsuTakashi WashioYoshiharu MatsuuraKazunori TomonoNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-8 (2021) |
| institution |
DOAJ |
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DOAJ |
| language |
EN |
| topic |
Science Q |
| spellingShingle |
Science Q Masateru Taniguchi Shohei Minami Chikako Ono Rina Hamajima Ayumi Morimura Shigeto Hamaguchi Yukihiro Akeda Yuta Kanai Takeshi Kobayashi Wataru Kamitani Yutaka Terada Koichiro Suzuki Nobuaki Hatori Yoshiaki Yamagishi Nobuei Washizu Hiroyasu Takei Osamu Sakamoto Norihiko Naono Kenji Tatematsu Takashi Washio Yoshiharu Matsuura Kazunori Tomono Combining machine learning and nanopore construction creates an artificial intelligence nanopore for coronavirus detection |
| description |
Rapid, accurate and specific point-of-care diagnostics can help manage and contain fast-spreading infections. Here, the authors present a nanopore-based system that uses artificial intelligence to discriminate between four coronaviruses in saliva, with little need for sample pre-processing. |
| format |
article |
| author |
Masateru Taniguchi Shohei Minami Chikako Ono Rina Hamajima Ayumi Morimura Shigeto Hamaguchi Yukihiro Akeda Yuta Kanai Takeshi Kobayashi Wataru Kamitani Yutaka Terada Koichiro Suzuki Nobuaki Hatori Yoshiaki Yamagishi Nobuei Washizu Hiroyasu Takei Osamu Sakamoto Norihiko Naono Kenji Tatematsu Takashi Washio Yoshiharu Matsuura Kazunori Tomono |
| author_facet |
Masateru Taniguchi Shohei Minami Chikako Ono Rina Hamajima Ayumi Morimura Shigeto Hamaguchi Yukihiro Akeda Yuta Kanai Takeshi Kobayashi Wataru Kamitani Yutaka Terada Koichiro Suzuki Nobuaki Hatori Yoshiaki Yamagishi Nobuei Washizu Hiroyasu Takei Osamu Sakamoto Norihiko Naono Kenji Tatematsu Takashi Washio Yoshiharu Matsuura Kazunori Tomono |
| author_sort |
Masateru Taniguchi |
| title |
Combining machine learning and nanopore construction creates an artificial intelligence nanopore for coronavirus detection |
| title_short |
Combining machine learning and nanopore construction creates an artificial intelligence nanopore for coronavirus detection |
| title_full |
Combining machine learning and nanopore construction creates an artificial intelligence nanopore for coronavirus detection |
| title_fullStr |
Combining machine learning and nanopore construction creates an artificial intelligence nanopore for coronavirus detection |
| title_full_unstemmed |
Combining machine learning and nanopore construction creates an artificial intelligence nanopore for coronavirus detection |
| title_sort |
combining machine learning and nanopore construction creates an artificial intelligence nanopore for coronavirus detection |
| publisher |
Nature Portfolio |
| publishDate |
2021 |
| url |
https://doaj.org/article/7cfcb758d04548a9925462a3e647155b |
| work_keys_str_mv |
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