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 ...

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 ...

Background and objectives Lung cancer remains the leading cause of cancer-related mortality worldwide. Early detection of pulmonary nodules is crucial for timely diagnosis and effective treatment.

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 ...

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 ...

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 light-based sensor can spot incredibly tiny amounts of cancer biomarkers in blood, raising the possibility of earlier and simpler cancer detection. The technology merges DNA nanotechnology, ...

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 ...

Lung cancer symptoms are often non-specific, leading to late detection and misattribution to less severe conditions. The GO2 for Lung Cancer provides resources, policy advocacy, and access to clinical ...