Emergency Medicine

Evaluating the impact of artificial intelligence tools on the detection of chest injuries from medical imaging: A systematic review and meta-analysis.

BACKGROUND: There has been a growing interest in the clinical application of artificial intelligence (AI) tools in medical imaging to aid diagnosis. This study conducts a systematic review of existing literature and performs a meta-analysis to compare the diagnostic performance of unassisted clinicians (CU) with clinicians assisted with AI (CA) in detecting traumatic chest injuries on diagnostic i...

How threshold customisation affects the performance of a multiclass X-ray AI model for primary care triage: a retrospective study.

OBJECTIVES: To describe the structured process of threshold optimisation for a commercially available multiclass chest X-ray (CXR) deep learning model, to evaluate its diagnostic performance across different operating thresholds, and to estimate its potential operational impact within an artificial intelligence (AI)-enabled triage workflow in a primary care setting. DESIGN: Retrospective diagnosti...

Integrated AI-Driven Triage and Referral for Newcomer Mental Health in Ontario: Addressing Anxiety and Depression.

Systemic barriers, including language, navigation complexity, and long specialist wait-times, result in the under-utilization of mental health service...

Deep Learning and Machine Learning for Differentiation Between Contrast Extravasation and Hemorrhagic Transformation in Post-Thrombectomy Stroke CT.

BACKGROUND: Mechanical thrombectomy (MT) improves outcomes in acute ischemic stroke (AIS) but often results in hyperdensities on non-contrast CT (NCCT...

ChronicDPipredictor: an interpretable deep learning framework for chemical chronic and subchronic toxicity assessment.

Chronic and subchronic toxicity are very important endpoints for evaluating the long-term and medium-term toxicity of chemical substances. However, du...

Development and evaluation of a prediction model for adult ICU hemorrhage using only continuous cardiorespiratory data.

Develop and evaluate whether a model trained to detect the physiological signature of hemorrhage in ICU patients generalizes to other cohorts. App...

Mechanistic signatures of comorbid PTSD with cognitive impairment implicate cortisol-induced neural toxicity.

The men and women who worked in rescue and recovery operations at the 9/11 World Trade Center site are developing cognitive impairment (CI) at mid-lif...

Prediction of death in burn patients infected with antibiotic-resistant Staphylococcus aureus using machine learning based techniques.

Multiscale characterization of micro fracture connectivity and gas migration in volcanic reservoirs using µCT and hybrid learning segmentation.

Multimodal MRI reveals hypothalamic structural-functional alterations associated with bone mineral density loss in postmenopausal women.

Emerging evidence implicates central nervous system dysregulation in the pathogenesis of osteoporosis. However, the role of hypothalamic subregions - ...

Machine learning-based on model for explain risk of 24-hour death in critically ill patients in the prehospital setting: A retrospective cohort study.

This study aimed to develop and validate a machine learning-based model for predicting 24-hour mortality in critically ill patients using prehospital ...

Artificial intelligence and predictive analytics in obstetric anesthesia: early warning for maternal complications.

PURPOSE OF REVIEW: Maternal morbidity and mortality remain largely preventable, yet current risk-assessment tools identify only a fraction of women wh...

Pullulan-based semi-interpenetrating network hydrogel sensor for artificial intelligence-driven pressure recognition.

Hydrogel sensors have gained significant attention in recent years due to their ability to detect various stimuli. This work first employs a "one-pot ...

NPSA 2025 Presidential Address:Innovation, clinical translation, and leadership in surgery: From concept to impact.

Innovation is frequently invoked as an essential driver of progress in modern surgery, yet its definition, implementation, and leadership aspects rema...

Machine learning for hemodynamic instability prediction and hemorrhage management in trauma and perioperative care.

PURPOSE OF REVIEW: Hemodynamic instability and uncontrolled hemorrhage remain leading causes of preventable morbidity and mortality in trauma and peri...

Real-time, artificial intelligence-guided intraoperative resuscitation and fluid management in trauma anesthesia.

PURPOSE OF REVIEW: To synthesize recent advances in intraoperative resuscitation for trauma surgery, including fluid composition, transfusion threshol...

Re-envisioning the North American Biodosimetry Assessment Networking Group.

The RNCP/NIAID recommends the creation of a North American Biodosimetry Assessment Networking Group (BANG) by developing a blueprint for integrating t...

Facing the Silent Crisis: Suicidal Ideation and Suicide in the Nursing Profession.

BACKGROUND: This manuscript explores the silent yet urgent crisis of suicidal ideation and suicide within the nursing profession. Despite being one of...

Clinical impact of adopting an AI-driven opportunistic bone health screening software using routine X-ray.

OBJECTIVES: To evaluate the clinical impact of an artificial intelligence device, Rho, that opportunistically screens X-rays for low bone mineral dens...

Artificial intelligence on opportunistic computed tomography for predicting vertebral fracture risk in women undergoing estrogen deprivation therapy for breast cancer.

PURPOSE: Fracture risk prediction in women exposed to hormone deprivation therapies (HDTs) for breast cancer is challenging, since bone mineral densit...