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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...
Tallennettuna:
| Julkaisussa: | Open Heart |
|---|---|
| Päätekijät: | , , , |
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
BMJ Publishing Group
2020
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| Aiheet: | |
| Linkit: | 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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