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Automated interpretation of the coronary angioscopy with deep convolutional neural networks
BACKGROUND: Coronary angioscopy (CAS) is a useful modality to assess atherosclerotic changes, but interpretation of the images requires expert knowledge. Deep convolutional neural networks (DCNN) can be used for diagnostic prediction and image synthesis. METHODS: 107 images from 47 patients, who und...
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| 出版年: | Open Heart |
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| 主要な著者: | , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
BMJ Publishing Group
2020
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7228653/ https://ncbi.nlm.nih.gov/pubmed/32404485 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1136/openhrt-2019-001177 |
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