Application of EfficientNet‐B0 and GRU‐based deep learning on classifying the colposcopy diagnosis of precancerous cervical lesions
Abstract Background Colposcopy is indispensable for the diagnosis of cervical lesions. However, its diagnosis accuracy for high‐grade squamous intraepithelial lesion (HSIL) is at about 50%, and the accuracy is largely dependent on the skill and experience of colposcopists. The advancement in computa...
| Published in: | Cancer Medicine |
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| Main Authors: | , , , , , , |
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-04-01
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| Subjects: | |
| Online Access: | https://doi.org/10.1002/cam4.5581 |
