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 …

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 …

Background Colposcopy is widely used to detect cervical cancer, but developing countries
lack the experienced colposcopists necessary for accurate diagnosis. Artificial intelligence …

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 …

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, the fourth most common cancer among women worldwide, often proves
fatal and stems from precursor lesions caused by high-risk human papillomavirus (HR-HPV) …

Background Deep learning has presented considerable potential and is gaining more
importance in computer assisted diagnosis. As the gold standard for pathologically …

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 …

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 …

Artificial intelligence has enabled the automated diagnosis of several cancer types. We
aimed to develop and validate deep learning models that automatically classify cervical …