Latest AI and machine learning research in prevention of medical errors for healthcare professionals.
BACKGROUND: Tobacco use disorder (TUD) remains the leading preventable cause of death globally, yet fewer than one-third of users receive guideline-concordant care due to workforce shortages and training gaps. Emerging artificial intelligence (AI) systems, particularly large language models (LLMs), may help expand access to evidence-based cessation support, but their clinical competence remains in...
Large language models (LLMs) are poised to become a ubiquitous feature of everyday life, mediating communication, decision making, and information curation across nearly every domain. Within psychiatry and psychology, the attention has largely been on bespoke therapeutic applications, sometimes narrowly focused and often diagnostically siloed, rather than on the broader reality that individuals wi...
BACKGROUND: The integration of artificial intelligence (AI) into clinical practice is contingent on public trust. This trust often depends on physicia...
Artificial intelligence (AI) is no longer just a passing trend. It is slowly becoming an integral part of our daily lives and our medical practice. AI...
INTRODUCTION: HIV/sexually transmitted infection (STI) prevention interventions are only modestly successful among youth, particularly for young peopl...
INTRODUCTION: Intensive care unit (ICU) visiting restrictions in hospitals, implemented due to infection control and other factors, limited contact be...
Accurate prediction of pediatric epidemic infectious diseases is critical for effective prevention and personalized treatment. Herein, we developed a ...
UNLABELLED: Timely diagnosis and intervention in colorectal cancer are critical to improving patient outcomes and limiting disease progression. Screen...
BACKGROUND: Type 2 diabetes mellitus (T2DM) substantially increases the risk of macrovascular complications, including coronary artery disease, cerebr...
The BETTER4U project (Preventing Obesity through Biologically and bEhaviorally Tailored inTERventions for You) is a Horizon Europe initiative (GAP 101...
BACKGROUND: Radiotherapy planning traditionally requires a dedicated simulation CT (sCT), which can introduce delays in initiating treatment. This is ...
MRI plays a central role in the diagnosis and management of multiple sclerosis (MS), and the 2017 revised McDonald criteria have improved the sensitiv...
Fetal and neonatal alloimmune thrombocytopenia (FNAIT) is a major cause of severe thrombocytopenia, intracranial hemorrhage, and long-term neurologica...
PURPOSE OF REVIEW: Machine learning predictive modeling can support scalable prevention of suicide-related behavior (SRB). SAFEGUARD is a three-pronge...
Geological disasters, as major natural hazards threatening regional sustainable development, have made risk assessment and planning governance core is...
Artificial intelligence (AI) is rapidly transforming healthcare delivery, logistics, and operational decision-making across the Military Health System...
AIMS: We sought to investigate the current state of education to support person- and whānau-centred care (PWCC) in our setting and to inform a new app...
Suicide among older adults remains a major global public health concern, particularly acute in South Korea. Effective prevention requires prediction m...
STUDY OBJECTIVE: Artificial Intelligence (AI) is being increasingly applied in medical education, yet its role in developing complex communication ski...
Artificial intelligence (AI) is a tool that could provide useful prevention strategies for people at risk of suicide. However, there are many ethical ...