What has happened in machine learning lately, and what does it mean for the future of
medical image analysis? Machine learning has witnessed a tremendous amount of attention …

Simple Summary Transfer learning plays a major role in medical image analyses; however,
obtaining adequate training image datasets for machine learning algorithms can be …

In the world, in the past recent five years, breast cancer is diagnosed about 7.8 million
women's and making it the most widespread cancer, and it is the second major reason for …

There is an increasing prevalence of Vascular Cognitive Impairment (VCI) worldwide, and
several studies have suggested that Chronic Cerebral Hypoperfusion (CCH) plays a critical …

Artificial intelligence (AI), particularly deep learning algorithms, is gaining extensive attention
for its excellent performance in image-recognition tasks. They can automatically make a …

Computer-aided diagnosis (CAD) has been a popular area of research and development in
the past few decades. In CAD, machine learning methods and multidisciplinary knowledge …

Purpose We aimed to use deep learning with convolutional neural network (CNN) to
discriminate between benign and malignant breast mass images from ultrasound. Materials …

Purpose The purpose of this study was to assess the perception, knowledge, wishes and
expectations of a sample of French radiologists towards the rise of artificial intelligence (AI) …

Scoliosis is a common disease of the spine and requires regular monitoring due to its
progressive properties. A preferred indicator to assess scoliosis is by the Cobb angle, which …

Ensemble methods try to improve performance via integrating different kinds of input data,
features, or learning algorithms. In addition to other areas, they are finding their applications …