Background Ultra–low-dose (ULD) CT could facilitate the clinical implementation of large-
scale lung cancer screening while minimizing the radiation dose. However, traditional image …

Identification of novel non‐invasive biomarkers is critical for the early diagnosis of lung
adenocarcinoma (LUAD), especially for the accurate classification of pulmonary nodule …

Background Solid components of part-solid nodules (PSNs) at CT are reflective of invasive
adenocarcinoma, but studies describing radiomic features of PSNs and the perinodular …

Rationale: The management of indeterminate pulmonary nodules (IPNs) remains
challenging, resulting in invasive procedures and delays in diagnosis and treatment …

Pulmonary nodules are managed on the basis of their size and morphologic characteristics.
Radiologists are familiar with assessing nodule size by measuring diameter using manually …

Computed tomography (CT) screening is an effective way for early detection of lung cancer
in order to improve the survival rate of such a deadly disease. For more than two decades …

Pulmonary nodules are a common finding on CT scans of the chest. In the United Kingdom,
management should follow British Thoracic Society Guidelines, which were published in …

Please see the Editorial Comment by Vicky Goh discussing this article. Interest in artificial
intelligence (AI) applications for lung nodules continues to grow among radiologists …

Objective Address model drift in a machine learning (ML) model for predicting diagnostic
imaging follow-up using data augmentation with more recent data versus retraining new …

Objective To evaluate whether an imaging classifier for radiology practice can improve lung
nodule classification and follow-up. Methods A machine learning classifier was developed …