Cancer diagnoses traditionally require invasive or labor-intensive procedures such as tissue biopsies. Researchers at the Ludwig-Maximilians-Universität München (LMU) have now reported on a method ...

Novel Graph Neural Network (N-GNN) Model Achieves Superior Accuracy in Early Lung Cancer Detection, Paving the Way for Enhanced Diagnostic Capabilities. The research, a collaboration between BioMark's ...

OXFORD, England & TORONTO--(BUSINESS WIRE)--Oxford Cancer Analytics (OXcan), the medtech company developing blood tests for early cancer detection using advanced proteomics and AI, today announced it ...

We combined natural language processing and large language models with state-of-the-art machine learning techniques and approaches to treat unbalanced data sets and determine the best solution to ...

Development and Validation of an Ipsilateral Breast Tumor Recurrence Risk Estimation Tool Incorporating Real-World Data and Evidence From Meta-Analyses: A Retrospective Multicenter Cohort Study Data ...

SAN DIEGO, APRIL 20, 2026 ― An artificial intelligence (AI) model developed by researchers at The University of Texas MD Anderson Cancer Center demonstrated the ability to accurately predict responses ...

Please provide your email address to receive an email when new articles are posted on . Machine learning models can predict which patients receiving lung cancer therapy may need urgent care visits.

SAN ANTONIO--(BUSINESS WIRE)--bioAffinity Technologies, Inc. (Nasdaq: BIAF; BIAFW), a biotechnology company focused on noninvasive diagnostics and early cancer detection, announces that its CyPath® ...

COPENHAGEN, Denmark — Screening individuals for lung cancer with low-dose CT without preselection based on their risk profile is associated with a substantial reduction in lung cancer-specific ...