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Deep learning-enabled medical computer vision
A decade of unprecedented progress in artificial intelligence (AI) has demonstrated the potential for many fields—including medicine—to benefit from the insights that AI techniques can extract from data. Here we survey recent progress in the development of modern computer vision techniques—powered b...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7794558/ https://www.ncbi.nlm.nih.gov/pubmed/33420381 http://dx.doi.org/10.1038/s41746-020-00376-2 |
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author | Esteva, Andre Chou, Katherine Yeung, Serena Naik, Nikhil Madani, Ali Mottaghi, Ali Liu, Yun Topol, Eric Dean, Jeff Socher, Richard |
author_facet | Esteva, Andre Chou, Katherine Yeung, Serena Naik, Nikhil Madani, Ali Mottaghi, Ali Liu, Yun Topol, Eric Dean, Jeff Socher, Richard |
author_sort | Esteva, Andre |
collection | PubMed |
description | A decade of unprecedented progress in artificial intelligence (AI) has demonstrated the potential for many fields—including medicine—to benefit from the insights that AI techniques can extract from data. Here we survey recent progress in the development of modern computer vision techniques—powered by deep learning—for medical applications, focusing on medical imaging, medical video, and clinical deployment. We start by briefly summarizing a decade of progress in convolutional neural networks, including the vision tasks they enable, in the context of healthcare. Next, we discuss several example medical imaging applications that stand to benefit—including cardiology, pathology, dermatology, ophthalmology–and propose new avenues for continued work. We then expand into general medical video, highlighting ways in which clinical workflows can integrate computer vision to enhance care. Finally, we discuss the challenges and hurdles required for real-world clinical deployment of these technologies. |
format | Online Article Text |
id | pubmed-7794558 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-77945582021-01-21 Deep learning-enabled medical computer vision Esteva, Andre Chou, Katherine Yeung, Serena Naik, Nikhil Madani, Ali Mottaghi, Ali Liu, Yun Topol, Eric Dean, Jeff Socher, Richard NPJ Digit Med Review Article A decade of unprecedented progress in artificial intelligence (AI) has demonstrated the potential for many fields—including medicine—to benefit from the insights that AI techniques can extract from data. Here we survey recent progress in the development of modern computer vision techniques—powered by deep learning—for medical applications, focusing on medical imaging, medical video, and clinical deployment. We start by briefly summarizing a decade of progress in convolutional neural networks, including the vision tasks they enable, in the context of healthcare. Next, we discuss several example medical imaging applications that stand to benefit—including cardiology, pathology, dermatology, ophthalmology–and propose new avenues for continued work. We then expand into general medical video, highlighting ways in which clinical workflows can integrate computer vision to enhance care. Finally, we discuss the challenges and hurdles required for real-world clinical deployment of these technologies. Nature Publishing Group UK 2021-01-08 /pmc/articles/PMC7794558/ /pubmed/33420381 http://dx.doi.org/10.1038/s41746-020-00376-2 Text en © The Author(s) 2021 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/. |
spellingShingle | Review Article Esteva, Andre Chou, Katherine Yeung, Serena Naik, Nikhil Madani, Ali Mottaghi, Ali Liu, Yun Topol, Eric Dean, Jeff Socher, Richard Deep learning-enabled medical computer vision |
title | Deep learning-enabled medical computer vision |
title_full | Deep learning-enabled medical computer vision |
title_fullStr | Deep learning-enabled medical computer vision |
title_full_unstemmed | Deep learning-enabled medical computer vision |
title_short | Deep learning-enabled medical computer vision |
title_sort | deep learning-enabled medical computer vision |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7794558/ https://www.ncbi.nlm.nih.gov/pubmed/33420381 http://dx.doi.org/10.1038/s41746-020-00376-2 |
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