The interest in machine learning (ML) has grown tremendously in recent years, partly due to
the performance leap that occurred with new techniques of deep learning, convolutional …

Radiomics is a technique that extracts quantitative features from medical images using data‐
characterization algorithms. Radiomic features can be used to identify tissue characteristics …

Objective The aim of this study was to identify the most important features and assess their
discriminative power in the classification of the subtypes of NSCLC. Methods This study …

Context.—Recent developments in machine learning have stimulated intense interest in
software that may augment or replace human experts. Machine learning may impact …

Rationale and Objectives Histological subtypes of lung cancers are critical for clinical
treatment decision. In this study, we attempt to use 3D deep learning and radiomics methods …

Simple Summary This work presents initial results for differentiating two major non-small cell
lung cancer (NSCLC) subtypes by exploring cross-scale associations between Computed …

There is a critical need for development of improved methods capable of accurately
predicting the RAS (KRAS and NRAS) and BRAF gene mutation status in patients with …

Purpose To develop handcrafted radiomics (HCR) and deep learning (DL) based automated
diagnostic tools that can differentiate between idiopathic pulmonary fibrosis (IPF) and non …

Background Non-invasive discrimination between lung squamous cell carcinoma (LUSC)
and lung adenocarcinoma (LUAD) subtypes of non-small-cell lung cancer (NSCLC) could …

Objective The aim of this article is to review the current applications of artificial intelligence in
thoracic surgery, from diagnosis and pulmonary disease management, to preoperative risk …