Journal article 534 views 102 downloads
Practical machine learning for disease diagnosis
Cell Reports Methods, Volume: 1, Issue: 6, Start page: 100103
Swansea University Author: Huw Summers
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DOI (Published version): 10.1016/j.crmeth.2021.100103
Abstract
Deep learning neural networks are a powerful tool in the analytical toolbox of modern microscopy, but they come with an exacting requirement for accurately annotated, ground truth cell images. Otesteanu et al. (2021) elegantly streamline this process, implementing network training by using patient-l...
Published in: | Cell Reports Methods |
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ISSN: | 2667-2375 |
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Elsevier BV
2021
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URI: | https://cronfa.swan.ac.uk/Record/cronfa58659 |
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2022-12-17T09:39:43.8489744 v2 58659 2021-11-15 Practical machine learning for disease diagnosis a61c15e220837ebfa52648c143769427 0000-0002-0898-5612 Huw Summers Huw Summers true false 2021-11-15 MEDE Deep learning neural networks are a powerful tool in the analytical toolbox of modern microscopy, but they come with an exacting requirement for accurately annotated, ground truth cell images. Otesteanu et al. (2021) elegantly streamline this process, implementing network training by using patient-level rather than cell-level disease classification. Journal Article Cell Reports Methods 1 6 100103 Elsevier BV 2667-2375 25 10 2021 2021-10-25 10.1016/j.crmeth.2021.100103 COLLEGE NANME Biomedical Engineering COLLEGE CODE MEDE Swansea University 2022-12-17T09:39:43.8489744 2021-11-15T10:51:04.1653916 Faculty of Science and Engineering School of Engineering and Applied Sciences - Biomedical Engineering Huw Summers 0000-0002-0898-5612 1 58659__21738__20f5fdae844e4f8abf365072ebd86c09.pdf 58659.pdf 2021-11-30T16:34:07.7766753 Output 426805 application/pdf Version of Record true Copyright: 2021 The Author(s). This is an open access article under the CC BY-NC-ND license true eng http://creativecommons.org/licenses/by-nc-nd/4.0/ |
title |
Practical machine learning for disease diagnosis |
spellingShingle |
Practical machine learning for disease diagnosis Huw Summers |
title_short |
Practical machine learning for disease diagnosis |
title_full |
Practical machine learning for disease diagnosis |
title_fullStr |
Practical machine learning for disease diagnosis |
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Practical machine learning for disease diagnosis |
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Practical machine learning for disease diagnosis |
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a61c15e220837ebfa52648c143769427 |
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a61c15e220837ebfa52648c143769427_***_Huw Summers |
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Huw Summers |
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Huw Summers |
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Cell Reports Methods |
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100103 |
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2021 |
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Swansea University |
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2667-2375 |
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10.1016/j.crmeth.2021.100103 |
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Elsevier BV |
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description |
Deep learning neural networks are a powerful tool in the analytical toolbox of modern microscopy, but they come with an exacting requirement for accurately annotated, ground truth cell images. Otesteanu et al. (2021) elegantly streamline this process, implementing network training by using patient-level rather than cell-level disease classification. |
published_date |
2021-10-25T04:15:21Z |
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11.028798 |