Deep learning (DL) has the potential to transform medical diagnostics. However, the
diagnostic accuracy of DL is uncertain. Our aim was to evaluate the diagnostic accuracy of …

Purpose To assess generalizability of published deep learning (DL) algorithms for radiologic
diagnosis. Materials and Methods In this systematic review, the PubMed database was …

Screening mammography aims to identify breast cancer at earlier stages of the disease,
when treatment can be more successful. Despite the existence of screening programmes …

The number of publications on deep learning for cancer diagnostics is rapidly increasing,
and systems are frequently claimed to perform comparable with or better than clinicians …

Background Deep learning offers considerable promise for medical diagnostics. We aimed
to evaluate the diagnostic accuracy of deep learning algorithms versus health-care …

One of the most promising areas of health innovation is the application of artificial
intelligence (AI), primarily in medical imaging. This article provides basic definitions of terms …

Background Artificial intelligence (AI) systems performing at radiologist-like levels in the
evaluation of digital mammography (DM) would improve breast cancer screening accuracy …

Abstract Background and Objective Computer aided diagnosis systems based on deep
learning and medical imaging is increasingly becoming research hotspots. At the moment …

Major advances in diagnostic technologies are offering unprecedented insight into the
condition of the retina and beyond ocular disease. Digital images providing millions of …

Deep learning is a class of machine learning methods that are gaining success and
attracting interest in many domains, including computer vision, speech recognition, natural …