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 ...

By Priyanjana Pramanik, MSc. Researchers reveal why lung cancer in people who never smoked is increasing and explore how ...

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 ...

(a) Deep learning-based circulating exosome analysis for lung cancer detection (copyright American Chemical Society, 2024); (b) The operational mechanism of the Förster resonance energy transfer (FRET ...

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 ...

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 ...

A new CRISPR-powered light sensor can detect the faintest whispers of cancer in a single drop of blood.

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.

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 ...

A New York City woman is using her lung cancer survival story to push for early detection, especially among nonsmokers and those in underserved communities. Colette Smith of the Bronx wrote a message ...

In a prospective imaging study of 200 adults with lung cancer, photon-counting CT reduced radiation exposure, yielded fewer ...