Recent advances and future perspectives of machine learning techniques offer promising
applications in medical imaging. Machine learning has the potential to improve different …

Although artificial intelligence (AI) has been a focus of medical research for decades, in the
last decade, the field of radiology has seen tremendous innovation and also public focus …

Abstract Machine learning is rapidly gaining importance in radiology. It allows for the
exploitation of patterns in imaging data and in patient records for a more accurate and …

Much attention has been given to machine learning and its perceived impact in radiology,
particularly in light of recent success with image classification in international competitions …

Worldwide interest in artificial intelligence (AI) applications, including imaging, is high and
growing rapidly, fueled by availability of large datasets (“big data”), substantial advances in …

The field of diagnostic decision support in radiology is undergoing rapid transformation with
the availability of large amounts of patient data and the development of new artificial …

Advances in both imaging and computers have synergistically led to a rapid rise in the
potential use of artificial intelligence in various radiological imaging tasks, such as risk …

Artificial intelligence (AI), machine learning, and deep learning are terms now seen
frequently, all of which refer to computer algorithms that change as they are exposed to more …

There have been tremendous advances in artificial intelligence (AI) and machine learning
(ML) within the past decade, especially in the application of deep learning to various …

Machine learning is a technique for recognizing patterns that can be applied to medical
images. Although it is a powerful tool that can help in rendering medical diagnoses, it can be …