Cervical cancer detection has witnessed significant advancements through the integration of deep learning techniques into medical imaging and diagnostic procedures. Modern deep learning methods ...

Gynecological cancers, including breast, ovarian, and cervical malignancies, account for a significant global health burden among women. The review outlines how a spectrum of machine learning (ML) ...

The AI model from IASST boasts a 98.02% accuracy, significantly improving early detection of cervical dysplasia.

Cervical cancer remains a major health threat for women globally, with the highest incidence in developing nations. Despite the availability of preventive measures, challenges such as limited ...

AI transforms cervical cancer screening by improving accuracy, speed, and early detection, offering better outcomes for women’s health and personalized care.

Hologic Inc. is teaming up with Google Cloud to use machine learning technologies to improve the accuracy and timeliness of cytology for cervical cancer screening. Marlborough, Mass.-based Hologic, ...

Most cervical cancers are caused by human papilloma virus (HPV), providing a convenient genetic marker of cancer-derived DNA that could be used to assess residual disease burden within plasma.