Artificial intelligence (AI) algorithms, particularly deep learning, have demonstrated
remarkable progress in image-recognition tasks. Methods ranging from convolutional neural …

Deep learning is the state-of-the-art machine learning approach. The success of deep
learning in many pattern recognition applications has brought excitement and high …

Deep learning algorithms promise to improve clinician workflows and patient outcomes.
However, these gains have yet to be fully demonstrated in real world clinical settings. In this …

The rapid development of deep learning, a family of machine learning techniques, has
spurred much interest in its application to medical imaging problems. Here, we develop a …

Intelligent agents are showing increasing promise for clinical decision-making in a variety of
healthcare settings. While a substantial body of work has contributed to the best strategies to …

Importance After the US Food and Drug Administration (FDA) approved computer-aided
detection (CAD) for mammography in 1998, and the Centers for Medicare and Medicaid …

The real cause of breast cancer is very challenging to determine and therefore early
detection of the disease is necessary for reducing the death rate due to risks of breast …

Objectives Performance of recently developed deep learning models for image classification
surpasses that of radiologists. However, there are questions about model performance …

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 …

Importance An increasing number of machine learning (ML)–based clinical decision support
systems (CDSSs) are described in the medical literature, but this research focuses almost …