Medical imaging plays a key role in evaluating and monitoring lung diseases such as
chronic obstructive pulmonary disease (COPD) and lung cancer. The application of artificial …

Radiomics has become a popular image analysis method in the last few years. Its key
hypothesis is that medical images harbor biological, prognostic and predictive information …

Introduction Lung cancer ranks second in new cancer cases and first in cancer-related
deaths worldwide. Precision medicine is working on altering treatment approaches and …

Artificial intelligence (AI) has increasingly been serving the field of radiology over the last 50
years. As modern medicine is evolving towards precision medicine, offering personalized …

Lung cancer is the leading cause of cancer-related deaths worldwide. It exhibits, at the
mesoscopic scale, phenotypic characteristics that are generally indiscernible to the human …

Medical imaging is the standard-of-care for early detection, diagnosis, treatment planning,
monitoring, and image-guided interventions of lung cancer patients. Most medical images …

Lung cancers exhibit strong phenotypic differences that can be visualized noninvasively by
medical imaging. Radiomics, a concept introduced in 2012, refers to the comprehensive …

Radiomics is a novel approach for optimizing the analysis massive data from medical
images to provide auxiliary guidance in clinical issues. Quantitative feature extraction is one …

Introduction: Radiomics extracts a large amount of quantitative information from medical
images using specific data characterization algorithms. This information, called radiomic …

Radiogenomics provide a large-scale data analytical framework that aims to understand the
broad multiscale relationships between the complex information encoded in medical images …