Artificial intelligence technology promises to redefine the practice of radiology. However, it exists in a nascent phase and remains largely untested in the clinical space. This nature is both a cause and consequence of the uncertain legal-regulatory...
Although recent scientific studies suggest that artificial intelligence (AI) could provide value in many radiology applications, much of the hard engineering work required to consistently realize this value in practice remains to be done. In this art...
Artificial intelligence (AI) and informatics promise to improve the quality and efficiency of diagnostic radiology but will require substantially more standardization and operational coordination to realize and measure those improvements. As radiolog...
The radiology reporting process is beginning to incorporate structured, semantically labeled data. Tools based on artificial intelligence technologies using a structured reporting context can assist with internal report consistency and longitudinal t...
This paper is concerned with the role of science and technology in helping to create change in society. Diagnostic radiology is an example of an activity that has undergone significant change due to such developments, which over the past 40 years hav...
Journal of medical imaging and radiation oncology
Aug 1, 2021
INTRODUCTION: The Royal Australian and New Zealand College of Radiologists (RANZCR) led the medical community in Australia and New Zealand in considering the impact of machine learning and artificial intelligence (AI) in health care. RANZCR identifie...
Tremendous advances in artificial intelligence (AI) in medical image analysis have been achieved in recent years. The integration of AI is expected to cause a revolution in various areas of medicine, including gastrointestinal (GI) pathology. Current...
Journal of gastroenterology and hepatology
Mar 1, 2021
Recently, radiomics and deep learning have gained attention as methods for computerized image analysis. Radiomics and deep learning can perform diagnostic or predictive tasks using high-dimensional image-derived features and have the potential to exp...
Artificial intelligence (AI) holds much promise for enabling highly desired imaging diagnostics improvements. One of the most limiting bottlenecks for the development of useful clinical-grade AI models is the lack of training data. One aspect is the ...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.