Abstract Machine learning (ML) is a burgeoning field of medicine with huge resources being
applied to fuse computer science and statistics to medical problems. Proponents of ML extol …

The remarkable success of deep learning has prompted interest in its application to medical
imaging diagnosis. Even though state-of-the-art deep learning models have achieved …

Machine learning (ML) is increasingly being used in image retrieval systems for medical
decision making. One application of ML is to retrieve visually similar medical images from …

The success of statistical machine learning (ML) methods made the field of Artificial
Intelligence (AI) so popular again, after the last AI winter. Meanwhile deep learning …

Abstract Machine learning (ML) is the fastest growing field in computer science, and health
informatics is among the greatest challenges. The goal of ML is to develop algorithms which …

Background Evaluation of interstitial lung disease (ILD) at CT is a challenging task that
requires experience and is subject to substantial interreader variability. Purpose To …

The discipline of radiology and diagnostic imaging has evolved greatly in recent years. We
have observed an exponential increase in the number of exams performed …

Over the past decades, medical image analytics was greatly facilitated by the explosion of
digital imaging techniques, where huge amounts of medical images were produced with …

Dermoscopy is a non-invasive skin imaging technique that permits visualization of features
of pigmented melanocytic neoplasms that are not discernable by examination with the …

Therapeutic activities of drugs are often influenced by co-administration of drugs that may
cause inevitable drug-drug interactions (DDIs) and inadvertent side effects. Prediction and …