Application of deep learning to the classification of uterine cervical squamous epithelial lesion from colposcopy images combined with HPV types
Y Miyagi, K Takehara, Y Nagayasu… - Oncology …, 2020 - spandidos-publications.com
The aim of the present study was to explore the feasibility of using deep learning, such as
artificial intelligence (AI), to classify cervical squamous epithelial lesions (SILs) from …
artificial intelligence (AI), to classify cervical squamous epithelial lesions (SILs) from …
Application of deep learning to the classification of uterine cervical squamous epithelial lesion from colposcopy images
Y Miyagi, K Takehara, T Miyake - … and clinical oncology, 2019 - spandidos-publications.com
The aim of the present study was to explore the feasibility of using deep learning as artificial
intelligence (AI) to classify cervical squamous epithelial lesions (SIL) from colposcopy …
intelligence (AI) to classify cervical squamous epithelial lesions (SIL) from colposcopy …
[HTML][HTML] Computer-aided diagnostic system based on deep learning for classifying colposcopy images
L Liu, Y Wang, X Liu, S Han, L Jia, L Meng… - Annals of …, 2021 - ncbi.nlm.nih.gov
Background Colposcopy is widely used to detect cervical cancer, but developing countries
lack the experienced colposcopists necessary for accurate diagnosis. Artificial intelligence …
lack the experienced colposcopists necessary for accurate diagnosis. Artificial intelligence …
Application of EfficientNet‐B0 and GRU‐based deep learning on classifying the colposcopy diagnosis of precancerous cervical lesions
X Chen, X Pu, Z Chen, L Li, KN Zhao, H Liu… - Cancer …, 2023 - Wiley Online Library
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 …
diagnosis accuracy for high‐grade squamous intraepithelial lesion (HSIL) is at about 50 …
Convolutional neural network-based classification of cervical intraepithelial neoplasias using colposcopic image segmentation for acetowhite epithelium
J Kim, CM Park, SY Kim, A Cho - Scientific Reports, 2022 - nature.com
Colposcopy is a test performed to detect precancerous lesions of cervical cancer. Since
cervical cancer progresses slowly, finding and treating precancerous lesions helps prevent …
cervical cancer progresses slowly, finding and treating precancerous lesions helps prevent …
Development and validation of artificial intelligence-based analysis software to support screening system of cervical intraepithelial neoplasia
YT Ouh, TJ Kim, W Ju, SW Kim, S Jeon, SN Kim… - Scientific Reports, 2024 - nature.com
Cervical cancer, the fourth most common cancer among women worldwide, often proves
fatal and stems from precursor lesions caused by high-risk human papillomavirus (HR-HPV) …
fatal and stems from precursor lesions caused by high-risk human papillomavirus (HR-HPV) …
The application of deep learning based diagnostic system to cervical squamous intraepithelial lesions recognition in colposcopy images
C Yuan, Y Yao, B Cheng, Y Cheng, Y Li, Y Li, X Liu… - Scientific reports, 2020 - nature.com
Background Deep learning has presented considerable potential and is gaining more
importance in computer assisted diagnosis. As the gold standard for pathologically …
importance in computer assisted diagnosis. As the gold standard for pathologically …
Classification of cervical neoplasms on colposcopic photography using deep learning
Colposcopy is widely used to detect cervical cancers, but experienced physicians who are
needed for an accurate diagnosis are lacking in developing countries. Artificial intelligence …
needed for an accurate diagnosis are lacking in developing countries. Artificial intelligence …
Comparison of machine and deep learning for the classification of cervical cancer based on cervicography images
Cervical cancer is the second most common cancer in women worldwide with a mortality
rate of 60%. Cervical cancer begins with no overt signs and has a long latent period, making …
rate of 60%. Cervical cancer begins with no overt signs and has a long latent period, making …
Automated diagnosis of cervical intraepithelial neoplasia in histology images via deep learning
Artificial intelligence has enabled the automated diagnosis of several cancer types. We
aimed to develop and validate deep learning models that automatically classify cervical …
aimed to develop and validate deep learning models that automatically classify cervical …
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