Latest AI and machine learning research in risk management for healthcare professionals.
BACKGROUND: Artificial intelligence (AI) is increasingly encountered in clinical care and medical education, but medical students' attitudes, perceptions, and self-reported familiarity have been assessed using heterogeneous survey instruments, AI referents, and response scales. Prior reviews often combined mixed health-profession populations or summarized central estimates without fully showing va...
BACKGROUND: The use of social media (SoMe) during crisis and disaster situations (CaDs) has gained increasing attention across disciplines. However, existing research is highly fragmented and often focused on technical aspects, with a limited understanding of how and which psychosocial information is derived from SoMe in CaDs. OBJECTIVE: This scoping review provides an overview of the current rese...
Children with autism spectrum disorder (ASD) face difficulties in expressing and recognizing emotions resulting in meltdowns and aggressive situations...
BACKGROUND: Cardiovascular disease (CVD) is a leading cause of death worldwide, making early risk prediction essential for improving outcomes. Althoug...
OBJECTIVE: To develop and internally validate an interpretable prognostic model for cumulative clinical pregnancy in women with diminished ovarian res...
BACKGROUND: With growing interest in ART, fertility preservation, and postmenopausal health of women, reproductive medicine is increasingly focused on...
The Darcy-Weisbach friction factor is used to determine the head losses occurring due to friction in pressurised pipes. It is defined by the Colebrook...
BACKGROUND: Current guidelines recommend pancolonic chromoendoscopy (pCE) over white light endoscopy (WLE) alone for colorectal neoplasia (CRN) detect...
AIMS: One in 10 patients present to the emergency department (ED) with symptoms of acute coronary syndrome (ACS). The 13-item ACS Symptom Checklist is...
OBJECTIVE: To evaluate the diagnostic accuracy and clinical reasoning of three frontier large language models (LLMs) across standardized pediatric gas...
Leadership has emerged as a core competency for Canadian radiologists navigating an era of challenges, including the integration of artificial intelli...
BACKGROUND: Pharmacovigilance aims to protect patient safety by identifying and managing adverse events associated with pharmaceuticals. Determining t...
CONTEXT: Statistical and artificial intelligence (AI)-based methods have informed clinical prognostication for decades, evolving into machine learning...
INTRODUCTION: Blood pressure treatment response is variable in individual patients, and the choice of medical therapy is often dependent on clinician ...
INTRODUCTION: Internationally, nursing students' awareness and familiarity with artificial intelligence (AI) remain a challenge as evidenced by the cu...
Accurate differentiation between benign and malignant thyroid nodules on ultrasound remains clinically important, yet interpretation is operator-depen...
BACKGROUND: Artificial intelligence (AI) is increasingly available to faculty and students, yet adoption remains uneven. Faculty report uncertainty ab...
Early ambulation following cardiovascular and thoracic surgery (CVTS) is associated with improved postoperative outcomes. However, barriers such as pa...
BACKGROUND: Large language models (LLMs) are increasingly embedded in conversational agents for cardiometabolic care. These systems could support self...
BACKGROUND: Artificial intelligence (AI)-based nursing interventions are increasingly being used to manage chronic illnesses; however, their definitiv...