AIMC Topic: Squamous Intraepithelial Lesions

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Molecular detection of hrHPV-induced high-grade squamous intraepithelial lesions of the cervix through a targeted RNA next generation sequencing assay.

Molecular medicine (Cambridge, Mass.)
BACKGROUND: Cervical cancer screening programs are increasingly relying on sensitive molecular approaches as primary tests to detect high-risk human papillomaviruses (hrHPV), the causative agents of cervix cancer. Although hrHPV infection is a pre-re...

Deep Learning in High-Resolution Anoscopy: Assessing the Impact of Staining and Therapeutic Manipulation on Automated Detection of Anal Cancer Precursors.

Clinical and translational gastroenterology
INTRODUCTION: High-resolution anoscopy (HRA) is the gold standard for detecting anal squamous cell carcinoma (ASCC) precursors. Preliminary studies on the application of artificial intelligence (AI) models to this modality have revealed promising res...

Accurate deep learning model using semi-supervised learning and Noisy Student for cervical cancer screening in low magnification images.

PloS one
Deep learning technology has been used in the medical field to produce devices for clinical practice. Deep learning methods in cytology offer the potential to enhance cancer screening while also providing quantitative, objective, and highly reproduci...

Artificial intelligence-assisted fast screening cervical high grade squamous intraepithelial lesion and squamous cell carcinoma diagnosis and treatment planning.

Scientific reports
Every year cervical cancer affects more than 300,000 people, and on average one woman is diagnosed with cervical cancer every minute. Early diagnosis and classification of cervical lesions greatly boosts up the chance of successful treatments of pati...