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Smartphone-based platforms implementing microfluidic detection with image-based artificial intelligence
The frequent outbreak of global infectious diseases has prompted the development of rapid and effective diagnostic tools for the early screening of potential patients in point-of-care testing scenarios. With advances in mobile computing power and microfluidic technology, the smartphone-based mobile...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10007670/ https://www.ncbi.nlm.nih.gov/pubmed/36906581 http://dx.doi.org/10.1038/s41467-023-36017-x |
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author | Wang, Bangfeng Li, Yiwei Zhou, Mengfan Han, Yulong Zhang, Mingyu Gao, Zhaolong Liu, Zetai Chen, Peng Du, Wei Zhang, Xingcai Feng, Xiaojun Liu, Bi-Feng |
author_facet | Wang, Bangfeng Li, Yiwei Zhou, Mengfan Han, Yulong Zhang, Mingyu Gao, Zhaolong Liu, Zetai Chen, Peng Du, Wei Zhang, Xingcai Feng, Xiaojun Liu, Bi-Feng |
author_sort | Wang, Bangfeng |
collection | PubMed |
description | The frequent outbreak of global infectious diseases has prompted the development of rapid and effective diagnostic tools for the early screening of potential patients in point-of-care testing scenarios. With advances in mobile computing power and microfluidic technology, the smartphone-based mobile health platform has drawn significant attention from researchers developing point-of-care testing devices that integrate microfluidic optical detection with artificial intelligence analysis. In this article, we summarize recent progress in these mobile health platforms, including the aspects of microfluidic chips, imaging modalities, supporting components, and the development of software algorithms. We document the application of mobile health platforms in terms of the detection objects, including molecules, viruses, cells, and parasites. Finally, we discuss the prospects for future development of mobile health platforms. |
format | Online Article Text |
id | pubmed-10007670 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-100076702023-03-13 Smartphone-based platforms implementing microfluidic detection with image-based artificial intelligence Wang, Bangfeng Li, Yiwei Zhou, Mengfan Han, Yulong Zhang, Mingyu Gao, Zhaolong Liu, Zetai Chen, Peng Du, Wei Zhang, Xingcai Feng, Xiaojun Liu, Bi-Feng Nat Commun Review Article The frequent outbreak of global infectious diseases has prompted the development of rapid and effective diagnostic tools for the early screening of potential patients in point-of-care testing scenarios. With advances in mobile computing power and microfluidic technology, the smartphone-based mobile health platform has drawn significant attention from researchers developing point-of-care testing devices that integrate microfluidic optical detection with artificial intelligence analysis. In this article, we summarize recent progress in these mobile health platforms, including the aspects of microfluidic chips, imaging modalities, supporting components, and the development of software algorithms. We document the application of mobile health platforms in terms of the detection objects, including molecules, viruses, cells, and parasites. Finally, we discuss the prospects for future development of mobile health platforms. Nature Publishing Group UK 2023-03-11 /pmc/articles/PMC10007670/ /pubmed/36906581 http://dx.doi.org/10.1038/s41467-023-36017-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Review Article Wang, Bangfeng Li, Yiwei Zhou, Mengfan Han, Yulong Zhang, Mingyu Gao, Zhaolong Liu, Zetai Chen, Peng Du, Wei Zhang, Xingcai Feng, Xiaojun Liu, Bi-Feng Smartphone-based platforms implementing microfluidic detection with image-based artificial intelligence |
title | Smartphone-based platforms implementing microfluidic detection with image-based artificial intelligence |
title_full | Smartphone-based platforms implementing microfluidic detection with image-based artificial intelligence |
title_fullStr | Smartphone-based platforms implementing microfluidic detection with image-based artificial intelligence |
title_full_unstemmed | Smartphone-based platforms implementing microfluidic detection with image-based artificial intelligence |
title_short | Smartphone-based platforms implementing microfluidic detection with image-based artificial intelligence |
title_sort | smartphone-based platforms implementing microfluidic detection with image-based artificial intelligence |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10007670/ https://www.ncbi.nlm.nih.gov/pubmed/36906581 http://dx.doi.org/10.1038/s41467-023-36017-x |
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