Emergency Medicine

Non-invasive classification of coronary perfusion pressure during CPR using smartphone-based skin video and deep learning.

BACKGROUND AND OBJECTIVE: Coronary perfusion pressure (CPP) is an important determinant of myocardial blood flow and an indicator during cardiopulmonary resuscitation (CPR). However, conventional CPP monitoring methods are invasive and unsuitable for out-of-hospital settings. This study proposes a non-invasive approach to classify CPP levels using skin video recorded with a smartphone camera and d...

A pipeline for developing AI-driven models to predict molecular initiating events: a case study on neural tube defects.

Adverse Outcome Pathways (AOPs) describe the sequence of molecular and cellular events that lead to toxicity. Each pathway begins with a Molecular Initiating Event (MIE) and ends in an Adverse Outcome. Early identification of chemical activity on MIE-relevant protein targets supports first-line toxicity assessment and helps researchers prioritize mechanisms for subsequent experimental investigatio...

Exploratory prediction model for deep vein thrombosis in intensive care patients after anticoagulation therapy: An observational study.

BACKGROUND: Despite low-molecular-weight heparin (LMWH) prophylaxis, the incidence of deep vein thrombosis (DVT) remains high in intensive care unit (...

Comments on: "the use of machine learning in predicting clinical outcomes in emergency pre-examination triage: A systematic review of the literature".

Acceptable accuracy for medical AI: a survey of physicians and the general population in Sweden.

OBJECTIVES: To identify the lowest sensitivity and specificity that physicians and the general population consider acceptable for medical artificial i...

Clinical applications of EEG connectivity in acute brain injuries: A systematic review.

OBJECTIVE: While connectivity methods have been widely studied as predictors of recovery in chronic disorders of consciousness (DoC), evidence for EEG...

Current applications and challenges of artificial intelligence applied to diagnostics in pediatric musculoskeletal imaging.

The use of artificial intelligence (AI) in pediatric musculoskeletal imaging has undergone significant expansion over the past few years. Until recent...

An inventory of emergency department information systems (EDIS) in Canada: Benchmarking system functionality and technology readiness.

OBJECTIVES: Emergency Department Information Systems (EDIS) are essential digital technology used in Emergency Departments (ED). Modern EDIS provide e...

Sonogenetics for Precision Medicine: A Focus on Immunoengineering and Genome Engineering.

Ultrasound can penetrate centimetres of soft tissue, focus energy with millimetre precision, and operate safely under real-time image guidance. Levera...

Machine Learning-Based Phenotypes Combined with Comorbidity Burden in Cardiogenic Shock.

Correction: Artificial intelligence in pediatric dental trauma: do artificial intelligence chatbots address parental concerns effectively?

Heart Rate Variability via Poincaré Mapping as an Early Biomarker Post-Cardiac Arrest.

BACKGROUND: Predicting neurological outcomes following cardiac arrest remains challenging. This study introduces a two-stage approach that combines a ...

Explainable Prediction of ICU Transfer in Acute Pancreatitis: A Neural Network Model With SHAP Interpretability for Clinical Decision Support.

OBJECTIVE: Acute pancreatitis (AP) is a life-threatening disorder commonly observed in emergency departments. Patients with acute pancreatitis may nec...

The Sydney Triage to Admission Risk Tool With Artificial Intelligence (START-AI): Prediction of Inpatient Admission From Emergency Departments Using Ensemble Machine Learning.

OBJECTIVE: Use artificial intelligence (AI) to extend the Sydney triage to admission risk tool (START) and improve prediction of emergency department ...

Assessment of the risk of bacteremia in patients with hematologic malignancies in the emergency department: A comparative study between logistic regression and machine learning algorithms.

OBJECTIVE: To stratify the risk of bacteremia at the time of emergency department (ED) admission in patients with hematologic malignancies. To this en...

Real-time prediction of emergency department admissions using an AI model and its integration into hospital bed-planning.

OBJECTIVE: To design, validate, and implement a tool based on a machine-learning model capable of predicting emergency patient admissions in real time...

Reflections on the use of language models and artificial intelligence in emergency department triage.

Impact of a Digital Intelligence Platform on Radiology Workflow Efficiency and Patient Satisfaction: A Retrospective Cohort Study.

RATIONALE AND OBJECTIVES: Traditional radiology management models may face challenges in meeting the growing demand for medical imaging services, pote...

A guide to plant breeding for animal breeders.

Over the years, some animal breeding PhD graduates have found employment in major plant breeding companies, but this shift is often accompanied by cul...

Artificial Intelligence-Assisted Ultrasound in Austere Trauma Environments: Implications for Role 1 Military Medicine.

Pararescue jumpers are United States Air Force medical tactical operators who provide advanced trauma and prolonged casualty care in austere, high-ris...