Whole slide imaging enables the use of a wide array of digital image analysis tools that are
revolutionizing pathology. Recent advances in digital pathology and deep convolutional …

The aptness of machine learning (ML) to learn from large datasets, discover trends, and
make predictions has demonstrated its potential to metamorphose the medical field. Medical …

Deep learning approaches are widely used in the processing of medical images, including
histopathological images for cancer diagnosis. Therefore, the scientific and practical …

Digital pathology whole-slide images (WSIs) are large-size gigapixel images, and image
analysis based on deep learning artificial intelligence technology often involves pixelwise …

Cardiovascular disease is a widespread and potentially fatal condition that requires
proactive preventive measures and efficient screening approaches on a global scale. To …

Background Machine learning can operationalize the rich and complex data in electronic
patient records for exploratory pharmacovigilance endeavours. Objective The objective of …

The analysis of whole-slide pathological images is a major area of deep learning
applications in medicine. The automation of disease identification, prevention, diagnosis …

With the recent progress in deep learning, one of the common approaches to represent
images is extracting deep features. A primitive way to do this is by using off-the-shelf models …

Background Artificial intelligence (AI) is seen as one of the major disrupting forces in the
future healthcare system. However, the assessment of the value of these new technologies …

Accurate prediction of the likelihood of recurrence is important in the selection of
postoperative treatment for patients with early-stage breast cancer. In this study, we …