The application of deep learning techniques in lung nodule detection represents a significant advance in the early diagnosis and management of lung cancer. Recent developments have harnessed the power ...

Radiation therapy is a cornerstone of lung cancer treatment. But even when delivered with precision, radiation can damage healthy lung tissue. "Try as we might, when we deliver radiation to a cancer, ...

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 ...

Introduction Incidental pulmonary nodules (IPNs) are commonly encountered on chest radiographs (CXRs) performed for routine clinical indications and may represent early manifestations of significant ...

Survival outcomes in non-small cell lung cancer: Real-world analysis of immunotherapy era vs pre-immunotherapy era, with insights into treatment settings, racial disparities, and socioeconomic impacts ...

Researchers at Moffitt Cancer Center have identified distinct spatial tumor–immune ecosystems that predict whether patients with advanced non–small cell lung cancer will benefit from immunotherapy.

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 ...

Talk about a breath of fresh air. Researchers have developed a groundbreaking device that may one day make detecting lung cancer as easy as exhaling. “We built a screening tool that could allow ...

A new study published in JCO Clinical Cancer Informatics demonstrates that machine learning models incorporating patient-reported outcomes and wearable sensor data can predict which patients with ...