Latest AI and machine learning research in patient safety / risk management for healthcare professionals.
BACKGROUND/OBJECTIVES: The second mesiobuccal (MB2) canal detection in maxillary molars represents a notable challenge in endodontics. This scoping review (SR) attempts to map the existing research on artificial intelligence (AI)-based models in MB2 detection, delineating the current stage of clinical readiness and gaps associated with routine clinical implementation. METHODS: A comprehensive, ind...
BACKGROUND: Conversational voice AI assistants can automate postoperative follow-up calls in high-volume, low-complexity pathways such as cataract surgery but may widen health inequalities if language access and inclusive design are not built in. This patient and public involvement focus group was conducted to inform the Turkish-language adaptation of Dora ahead of a forthcoming multilingual clini...
BACKGROUND: Outcome prediction models for patients with ischemic stroke after endovascular thrombectomy (EVT) demonstrated the value of including post...
INTRODUCTION: Clinical trials have demonstrated the benefits of early detection of lung cancer (LC); however, the implementation of national LC screen...
BackgroundPosttraumatic stress disorder (PTSD) is common yet frequently underdiagnosed, in part due to barriers to systematic screening and the relian...
INTRODUCTION: Patients now arrive at the orthodontic consultation having already consulted a chatbot, yet the accuracy, quality and readability of the...
Misuse of statistical methods in biomedical research remains widespread, undermining scientific integrity and public health. Flawed analyses can lead ...
BACKGROUND: Artificial intelligence (AI) is increasingly encountered in clinical care and medical education, but medical students' attitudes, percepti...
BACKGROUND: Cardiovascular disease (CVD) is a leading cause of death worldwide, making early risk prediction essential for improving outcomes. Althoug...
Addressing stigma, mental health, and health care access challenges for people living with HIV requires a multifaceted approach. Generative artificial...
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...
Leadership has emerged as a core competency for Canadian radiologists navigating an era of challenges, including the integration of artificial intelli...
BACKGROUND: Artificial intelligence (AI) is increasingly available to faculty and students, yet adoption remains uneven. Faculty report uncertainty ab...
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...
Behçet's disease (BD) in childhood is characterised by recurrent inflammatory flares that can result in significant morbidity, most notably with ocula...
BACKGROUND: Enhancing the capacity to forecast tropical disease transmission, identify key risk factors, and support timely public health responses is...
BACKGROUND: Parents increasingly consult the internet, both websites and, more recently, artificial intelligence chatbots, for information on autism s...
Artificial intelligence (AI) is expanding in gastroenterology, particularly in endoscopy and imaging, where models support detection, classification, ...
Generative artificial intelligence (AI) is rapidly becoming embedded across scientific workflows, yet mechanisms for transparently documenting its use...