If AI I technology seeks to transform cancer care, it must solve three big needs: data, training and trust. Annemiek Snoeckx ...

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) ...

Researchers explore DNA methylation patterns for early ovarian cancer detection, aiming to improve survival rates through ...

Artificial intelligence relies on machine learning algorithms trained on massive datasets to make predictions—think of how ...

Standard concurrent chemoradiotherapy (CCRT) for cervical cancer achieves disease-free survival (DFS) in approximately 70% of ...

A research team at UCLA, led by Professor Aydogan Ozcan, has introduced BlurryScope, a compact, cost-effective scanning ...

New AI model detects and grades prostate cancer with 89% accuracy using MRI, cutting reliance on invasive biopsies and ...

Currently, the Molecular Twin platform leverages machine learning to make sense of complex multiomics datasets and identify which analytes could serve as predictive or prognostic biomarkers. Besides ...

The field of oncology has witnessed remarkable strides in early detection and treatment, yet cancer remains a formidable threat with high mortality rates ...