| | Reporting an AI-based diagnosis method that integrates Self-supervised Learning as a plugin module into a Multi-task Convolutional Neural Network for the automatic diagnosis of COVID-19 based on both CT and X-ray datasets. | The three CNNs applied to diagnose COVID-19 under single task schemes are : (i) VGG-19 (ii) ResNet-50 (iii) EfficientNet ✍ | 33518812
(Pattern Recognit)
| PMID | 33518812 Date of Publishing: 2021 Jun | | Title | Multi-task contrastive learning for automatic CT and X-ray diagnosis of COVID-19 | | Author(s) name | Li J, Zhao G et al. | | Journal | Pattern Recognit | | Impact factor | 7.35 Citation count: 14 |
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| NLM format |
| Li J, Zhao G, Tao Y, Zhai P, Chen H, He H, Cai T. Multi-task contrastive learning for automatic CT and X-ray diagnosis of COVID-19. Pattern Recognit. 2021 Jun;114:107848. PMID:33518812 |
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