Application of EfficientNet‐B0 and GRU‐based deep learning on classifying the colposcopy diagnosis o...
Application of EfficientNet‐B0 and GRU‐based deep learning on classifying the colposcopy diagnosis of precancerous cervical lesions
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United States: John Wiley & Sons, Inc
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English
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United States: John Wiley & Sons, Inc
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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 computational power made it possible for the application of art...
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Application of EfficientNet‐B0 and GRU‐based deep learning on classifying the colposcopy diagnosis of precancerous cervical lesions
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TN_cdi_doaj_primary_oai_doaj_org_article_b6a67f0332724bc4b9a152cacc4bdcdf
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_b6a67f0332724bc4b9a152cacc4bdcdf
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ISSN
2045-7634
E-ISSN
2045-7634
DOI
10.1002/cam4.5581
