INTRODUCTION: Methods to adopt artificial intelligence (AI) in healthcare clinical practice remain unclear. The potential for rapid integration of AI-enabled technologies across healthcare settings coupled with the growing digital divide in the healt...
BACKGROUND: The use of artificial intelligence (AI) technologies in radiography practice is increasing. As this advanced technology becomes more embedded in radiography systems and clinical practice, the role of radiographers will evolve. In the cont...
INTRODUCTION: Empirical data on the barriers limiting artificial intelligence (AI)'s impact on healthcare are scarce, particularly within the Canadian context. This study aims to address this gap by conducting a scoping review to identify and evaluat...
BACKGROUND: The rapid evolution of large language models (LLMs), such as Bidirectional Encoder Representations from Transformers (BERT; Google) and GPT (OpenAI), has introduced significant advancements in natural language processing. These models are...
BACKGROUND: Artificial intelligence broadly refers to computer systems that simulate intelligent behaviour with minimal human intervention. Emphasizing patient-centered care, research has explored patients' perspectives on artificial intelligence in ...
BACKGROUND: Artificial intelligence (AI) and machine learning (ML) methods are increasingly being applied in pediatric urology across a growing number of settings, with more extensive databases and wider interest for use in clinical practice. More th...
INTRODUCTION: Knee osteoarthritis (KOA) is a prevalent cause of disability, marked by functional impairments that significantly reduce quality of life. Emerging digital health tools-particularly artificial intelligence (AI) and motion tracking techno...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.