For the first time, researchers have used machine learning – a type of artificial intelligence (AI) – to identify the most important drivers of cancer survival in nearly all the countries in the world ...

A UVA Health physician helped shape new guidelines to expand at-home testing and prevent cancer before it starts.

According to the World Health Organization, each year cervical cancer impacts approximately 600,000 women throughout the ...

In a significant move aimed at strengthening regulatory clarity for cancer related medical technologies, the Central Drugs ...

Skin cancer is the most commonly diagnosed cancer in the United States, affecting one in five Americans during their lifetime. While basal cell carcinomas (BCCs) and squamous cell carcinomas (SCCs) ...

Abstract: HPV and various associated factors responsible for the development of cervical cancer in women. The only way to address the issue is through early screening and diagnosis for predicting ...

Researchers have developed an AI-based tool that accelerates the detection of kidney cancer. Its effectiveness was validated in a study published in Communications Medicine. Diagnosing kidney cancer ...

Deep learning CNN for automated cervical cancer detection using Pap smear images, with Streamlit deployment & Grad‑CAM. This project implements a deep learning Convolutional Neural Network (CNN) for ...

Objective: This study aims to develop and evaluate an artificial intelligence-based model for cervical cancer subtyping using whole-slide images (WSI), incorporating both patch-level and WSI-level ...

User interface of the Intelligent Digital Education Tool for Colposcopy (iDECO). This figure illustrates the main user interface of iDECO, a bilingual (Chinese and English) web-based platform for ...