BACKGROUND: Champions of AI-facilitated clinical documentation have suggested that the emergent technology may decrease the administrative loads of physicians, thereby reducing cognitive burden and forestalling burnout. Explorations of physicians' ex...
Deep learning has achieved immense success in computer vision and has the potential to help physicians analyze visual content for disease and other abnormalities. However, the current state of deep learning is very much a black box, making medical pr...
Venous thromboembolism (VTE) is the leading cause of preventable death in hospitalized patients. Artificial intelligence (AI) and machine learning (ML) can support guidelines recommending an individualized approach to risk assessment and prophylaxis....
Foundation machine learning models are deep learning models capable of performing many different tasks using different data modalities such as text, audio, images and video. They represent a major shift from traditional task-specific machine learning...
Building trustworthy and transparent image-based medical artificial intelligence (AI) systems requires the ability to interrogate data and models at all stages of the development pipeline, from training models to post-deployment monitoring. Ideally, ...
The skill of knowledge management empowers practitioners to efficiently integrate and apply knowledge in the clinical context. Current medical knowledge is vast which is beyond the human capacity to retain. Hence, modern-day learning is not just know...
BACKGROUND: Robotic spine surgery has continued to evolve since its US Food and Drug Administration approval in 2004, with products now including real-time video guidance and navigation during surgery. As the market for robotic surgical devices evolv...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.