The domain of investigation of radiomics consists of large-scale radiological image analysis
and association with biological or clinical endpoints. The purpose of the present study is to …

Artificial intelligence (AI) is emerging as a technology with the power to transform
established industries, and with applications from automated manufacturing to advertising …

Background Non-small-cell lung cancer (NSCLC) patients often demonstrate varying clinical
courses and outcomes, even within the same tumor stage. This study explores deep …

Radiomics extracts and mines large number of medical imaging features quantifying tumor
phenotypic characteristics. Highly accurate and reliable machine-learning approaches can …

Introduction “Radiomics” extracts and mines a large number of medical imaging features in a
non-invasive and cost-effective way. The underlying assumption of radiomics is that these …

We aimed to identify optimal machine-learning methods for radiomics-based prediction of
local failure and distant failure in advanced nasopharyngeal carcinoma (NPC). We enrolled …

Abstract Machine learning is an evolving branch of computational algorithms that are
designed to emulate human intelligence by learning from the surrounding environment …

Purpose Radiomics, which extract large amount of quantification image features from
diagnostic medical images had been widely used for prognostication, treatment response …

Advances in computing hardware and software platforms have led to the recent resurgence
in artificial intelligence (AI) touching almost every aspect of our daily lives by its capability for …

Background: Ultrasound (US) examination is helpful in the differential diagnosis of thyroid
nodules (malignant vs. benign), but its accuracy relies heavily on examiner experience …