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

By harnessing deep learning algorithms, AI is now able to replicate human-like interpretation of medical images, resulting in more accurate detection of cervical cancer.

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

Researchers at City of Hope and Translational Genomics Research Institute (TGen) have developed and tested an innovative machine-learning approach that could one day enable the earlier detection ...

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.