Radiomic analysis offers a powerful tool for the extraction of clinically relevant information
from radiologic imaging. Radiomics can be used to predict patient outcome through …

Breast Cancer (BC) is the common form of cancer in women. Its diagnosis and screening are
usually performed through different imaging modalities such as mammography, magnetic …

Simple Summary Recently, radiogenomics has played a significant role and offered a new
understanding of cancer's biology and behavior in response to standard therapy. It also …

From diagnostics to prognosis to response prediction, new applications for radiomics are
rapidly being developed. One of the fastest evolving branches involves linking imaging …

Although cancer often is referred to as “a disease of the genes,” it is indisputable that the
(epi) genetic properties of individual cancer cells are highly variable, even within the same …

Radiographic imaging continues to be one of the most effective and clinically useful tools
within oncology. Sophistication of artificial intelligence has allowed for detailed …

In medicine, particularly in radiology, there are great expectations in artificial intelligence
(AI), which can “see” more than human radiologists in regard to, for example, tumor size …

Background and purpose Radiomics allows extraction of quantifiable features from imaging.
This study performs a systematic review and meta-analysis of the performance of radiomics …

Purpose We aim to accurately differentiate between active pulmonary tuberculosis (TB) and
lung cancer (LC) based on radiomics and semantic features as extracted from pre-treatment …

Objectives: To predict the anaplastic lymphoma kinase (ALK) mutations in lung
adenocarcinoma patients non-invasively with machine learning models that combine …