Latest AI and machine learning research in risk management for healthcare professionals.
The increasing complexity of natural language reasoning in artificial intelligence necessitates a shift from opaque, black-box processing to transparent, interpretable decision-making. While large language models (LLMs) demonstrate remarkable generative capabilities, their reasoning pathways often remain implicit, which limits auditability in high-stakes settings. To address this issue, we propose...
BACKGROUND: Urogenital schistosomiasis caused by Schistosoma haematobium remains endemic in sub-Saharan Africa. Diagnosis traditionally relies on urine microscopy to detect parasite eggs; however, its sensitivity declines in low-intensity infections. Artificial intelligence (AI)-assisted image analysis offers a promising approach to automate egg detection and enhance diagnostic accuracy, but its p...
BACKGROUND: Cybersecurity attacks in healthcare have increased in number and severity over the last decade. Healthcare targets are ten times more valu...
BACKGROUND: "Empathy" is widely discussed in health and care settings and is increasingly claimed as an attribute of artificial intelligence (AI) syst...
INTRODUCTION: Point-of-care transthoracic echocardiography performed by anaesthetists can influence peri-operative management but is constrained by ti...
Hydrogen vehicles are facing significant challenges, including safety risks in the event of leakage, high costs associated with physical testing, and ...
OBJECTIVE: To conduct a systematic review and meta-analysis evaluating the diagnostic performance of medical image-based artificial intelligence (AI) ...
INTRODUCTION: This study aimed to evaluate the effectiveness of a generative artificial intelligence based simulated patient model in improving gyneco...
The rapid detection and precise classification of cerebrospinal fluid in acute leukemia patients constitute a crucial clinical imperative. Here, we pr...
BACKGROUND: Opioid overdose remains a leading cause of preventable death in the United States. Existing approaches to identify individuals at elevated...
BACKGROUND: Artificial intelligence (AI) has the potential to enhance patient safety, particularly in the prevention of in-hospital falls. Recent adva...
INTRODUCTION: Lung cancer (LC) is the leading cause of cancer-related mortality worldwide, primarily due to diagnosis at advanced stages. Although low...
Generative AI is rapidly entering patient education workflows, yet its safety profile for concussion management remains undefined. Utilizing the CHART...
BACKGROUND: MRI is essential for diagnosing and monitoring neurological diseases. Conventional protocols require multiple sequences to obtain compleme...
Policymakers are increasingly adopting artificial intelligence (AI) tools to support legislative decision-making, yet there is limited empirical under...
Tanzania has adopted artificial intelligence (AI)-assisted chest X-ray screening for tuberculosis (TB), including the use of CAD4TB version 6, which i...
BACKGROUND & AIMS: Transient elastography (TE) is routinely undertaken for non-invasive assessment of liver fibrosis and steatosis, but is limited by ...
As artificial intelligence (AI) becomes more integrated into public decision-making, its anthropomorphic features raise new questions about trust, acc...
Non-vesicular lipid transport contributes to the regulation of membrane composition and organelle function at membrane contact sites. OSBP-related pro...