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 ...

Model and clinical segmentation examples. (A) 71-year-old female with non-small cell lung cancer (NSCLC) from the internal test set. (B) 87-year-old male with NSCLC from the external test set. Both ...

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 ...

Using just one inhalation lung CT scan, a deep learning model can accurately diagnose and stage chronic obstructive pulmonary disease (COPD), according to a study published today in Radiology: ...

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 ...

AI tools can enhance diagnostic accuracy for ILDs, complementing radiologists' expertise and addressing their limitations. Machine learning relies on labeled data, while deep learning uses neural ...

Radiomics revealed hidden imaging patterns in sarcoidosis, correlating with disease severity, lung function, supporting ...

Comparative Analysis of Generative Pre-Trained Transformer Models in Oncogene-Driven Non–Small Cell Lung Cancer: Introducing the Generative Artificial Intelligence Performance Score This ...

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 ...

Dr George Owiti, a radiographer at Kericho County Hospital examines the Chest CT results of a patient admitted to the hospital. [James Wanzala, Standard] Despite recent breakthroughs that have ...