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 ...
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 ...
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 ...
Lung cancer remains one of the leading causes of cancer-related deaths worldwide, making early and accurate diagnosis essential for improving patient outcomes.
Lung cancer diagnosis relies heavily on interpreting complex computed tomography (CT) images, where accuracy can vary ...
Comparative Analysis of Generative Pre-Trained Transformer Models in Oncogene-Driven Non–Small Cell Lung Cancer: Introducing the Generative Artificial Intelligence Performance Score This ...
Artificial intelligence is enabling radiologists to extract valuable diagnostic information from routine chest imaging – ...
In patients with head and neck squamous cell carcinoma (HNSCC), low-dose CT achieved higher sensitivity than chest x-ray for detecting lung metastases and second primary lung cancer, but patients ...
A CT scan of healthy lungs looks typical in size with no inflammation, allowing the diaphragm to dome. Lungs with emphysema can look overinflated, with muscle loss, making the diaphragm misshapen. The ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results