Latest AI and machine learning research in patient safety / risk management for healthcare professionals.
The rapid evolution of generative artificial intelligence (genAI) has ushered in a new era of digital medical consultations, with patients turning to AI-driven tools for guidance. The emergence of Chinese-developed genAI models such as DeepSeek-R1 and Qwen-2.5 presented a challenge to the dominance of OpenAI's ChatGPT. The aim of this study was to benchmark the performance of Chinese genAI models ...
Timely recognition and initiation of basic life support (BLS) before emergency medical services arrive significantly improve survival rates and neurological outcomes. In an era where health information-seeking behaviors have shifted toward online sources, chatbots powered by generative artificial intelligence (AI) are emerging as potential tools for providing immediate health-related guidance. Thi...
Machine learning's (MLs) ability to capture intricate patterns makes it vital in neural engineering research. With its increasing use, ensuring the va...
INTRODUCTION: Accurate and timely discharge from the Post-Anesthesia Care Unit (PACU) is essential to prevent postoperative complications and optimize...
Artificial intelligence (AI) provides an opportunity to streamline tasks within academic medicine. Generative AI (genAI) models, specifically, have th...
BACKGROUND: Despite the rapid growth of research in artificial intelligence/machine learning (AI/ML), little is known about how often study results ar...
BACKGROUND: Soft-tissue and bone tumours (STBT) are rare, diagnostically challenging lesions with variable clinical behaviours and treatment approache...
BACKGROUND AND AIMS: Clinical hepatology research often faces limited data availability, underrepresentation of minority groups, and complex data-shar...
Posttraumatic stress disorder (PTSD) is a complex mental health condition triggered by exposure to traumatic events that leads to physical health prob...
IMPORTANCE: The rise of patient messages sent to clinicians via a patient portal has directly led to physician burnout and dissatisfaction, prompting ...
BACKGROUND/OBJECTIVES: This systematic literature review examines the quality of early clinical evaluation of artificial intelligence (AI) decision su...
In the current era of digitalization and greenization, it is of great importance to explore how enterprises utilize artificial intelligence (AI) to pr...
The CONSORT 2010 statement is a guideline that provides an evidence-based checklist of minimum reporting standards for randomized trials. With the rap...
Indigenous and local knowledge (ILK) is increasingly used along with scientific knowledge (SK) to understand climate change. The multi evidence base (...
Undergraduate students are often impacted by depression, anxiety, and stress. In this context, machine learning may support mental health assessment. ...
Artificial intelligence (AI) holds significant potential for enhancing quality of gastrointestinal (GI) endoscopy, but the adoption of AI in clinical ...
The review seeks to promote transparency in the availability of regulated AI-enabled Clinical Decision Support Systems (AI-CDSS) for mental healthcare...
ChatGPT has demonstrated significant potential in various aspects of medicine, including its performance on licensing examinations. In this study, we ...
In this article, the authors propose a repurposing of the concept of entrustment to help guide the use of artificial intelligence (AI) in health profe...
In recent years, artificial intelligence (AI) chatbots have made significant strides in generating human-like conversations. With AI's expanding capab...