Outside a screening program, early-stage lung cancer is generally diagnosed after the detection of incidental nodules in clinically ordered chest CT scans. Despite the advances in artificial ...
Slice thickness of computed tomography (CT) constitutes a vital determinant of image quality, which controls the spatial resolution of the volumetric image. Thinner slices yield images with higher ...
Immune infiltrate characterization and differential gene expression by RNA-sequencing analysis in patients with oncogene-addicted NSCLC with early progression under targeted therapy. This is an ASCO ...
COPD is widely recognized as a disease that affects more than just the lungs. Patients frequently experience systemic ...
An artificial intelligence (AI) deep learning tool that estimates the malignancy risk of lung nodules achieved high cancer detection rates while significantly reducing false-positive results. Results ...
Comparative Analysis of Generative Pre-Trained Transformer Models in Oncogene-Driven Non–Small Cell Lung Cancer: Introducing the Generative Artificial Intelligence Performance Score This ...
A new deep learning model shows promise in detecting and segmenting lung tumors, according to a study published today in Radiology. The findings of the study could have important implications for lung ...
ATS 2025, San Francisco – A deep learning model was able to predict future lung cancer risk from a single low-dose chest CT scan, according to new research published at the ATS 2025 International ...
A deep learning model was able to predict future lung cancer risk from a single low-dose chest CT scan, according to new research published at the ATS 2025 International Conference, and in American ...
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