Applications of machine learning (ML) methods have been used extensively to solve various
complex challenges in recent years in various application areas, such as medical, financial …

Machine learning with maximization (support) of separating margin (vector), called support
vector machine (SVM) learning, is a powerful classification tool that has been used for …

Abstract Machine learning is a branch of computer science that has the potential to transform
epidemiologic sciences. Amid a growing focus on “Big Data,” it offers epidemiologists new …

Chronic kidney disease (CKD) is among the top 20 causes of death worldwide and affects
approximately 10% of the world adult population. CKD is a disorder that disrupts normal …

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 …

Memristor crossbars are circuits capable of performing analog matrix-vector multiplications,
overcoming the fundamental energy efficiency limitations of digital logic. They have been …

Artificial intelligence (AI) is a field of computer science that aims to mimic human thought
processes, learning capacity, and knowledge storage. AI techniques have been applied in …

Automatic extraction of liver and tumor from CT volumes is a challenging task due to their
heterogeneous and diffusive shapes. Recently, 2D deep convolutional neural networks …

This study uses three machine learning algorithms including, support vector machine (SVM),
random forest (RF) and gradient boosting machine (GBM) in the appraisal of property prices …

The nature of manufacturing systems faces ever more complex, dynamic and at times even
chaotic behaviors. In order to being able to satisfy the demand for high-quality products in an …