Emergency Medicine

Graph Machine Learning Can Estimate Drug Concentrations in Whole Blood from Forensic Screening Results.

LC-HRMS is widely used in forensic toxicology for broad-scope screening. When a newly emerging or ra...

Development and Validation of a Machine Learning Model to Predict Oral Anticoagulant Use in Stroke From Prothrombin Time-International Normalized Ratio and Activated Partial Thromboplastin Time.

BACKGROUND: Timely recognition of oral anticoagulant use is critical in acute stroke but is often ha...

Practical adaptability of a pre-hospital prognostic prediction model for patients following out-of-hospital cardiac arrest during the COVID-19 pandemic.

OBJECTIVES: The overwhelmed situation under the COVID-19 pandemic has worsened the quality of emerge...

ABC-YOLO: Automated skin burn depth classification using YOLO architectures.

Accurate classification of skin burn depth is vital for determining appropriate treatment and accele...

FAD-MIL: a weakly supervised fracture detection model based on X-ray images.

Fractures are among the most common presentations to emergency and orthopedic services, yet radiogra...

Nanotoxicology meets smart polymers: advancing safety-by-design nanomaterials.

Smart polymers have played great role in enhancing nanomedical application areas in drug delivery, d...

A computational model for predicting shock in patients at risk of urosepsis after urolithiasis surgery.

Integration of detection and tracking networks for automated rib multiplanar reconstruction: a feasibility study for fracture diagnosis.

OBJECTIVE: Rib fractures are common yet time-consuming to diagnose. This study explores automation v...

Diagnostic performance and confidence of an optimized deep-learning algorithm for the detection of intracranial hemorrhages.

OBJECTIVES: To evaluate the performance of an optimized deep-learning-based algorithm (AI) for the d...

Integrating Large Language Models Into Trauma Education for Medical Students: Randomized Controlled Pilot Trial.

BACKGROUND: The exponential growth of medical knowledge presents a paradox for modern medical educat...

Artificial intelligence in emergency skeletal X-ray: post-deployment monitoring and clinical impact of incorrect AI results.

OBJECTIVES: This study evaluates the impact of the artificial intelligence (AI) application BoneView...

A metabolomics-driven machine learning model for osteoporosis risk prediction.

Osteoporosis, marked by decreased bone mineral density (BMD), poses a major public health concern by...

Decoding core molecular mechanisms of heat-stress tolerance in Brassica napus using transcriptomics and machine learning.

Integration of conventional bioinformatics approaches with advanced machine learning and explainable...

Accuracy of the large language model ChatGPT in adult emergency department triage: a systematic review and meta-analysis.

LAMB1 regulates COL3A1 and RAC1 expression during subchorionic hemorrhage progression.

BACKGROUND: Subchorionic hemorrhage (SCH) is characterized by a fluid-filled hypoechoic area in earl...

Life events extraction from healthcare notes for veteran acute suicide risk prediction.

OBJECTIVE: Predictive models of suicide risk have focused on features extracted from structured data...

Machine Learning in the ICU: Predicting Mortality in Patients with Carbapenem-Resistant Gram-Negative Bacilli Bloodstream Infections.

Background and ObjectiveMultidrug and carbapenem resistant gram-negative bacilli bloodstream infecti...

Artificial Intelligence-powered tiered early warning framework addressing high false alarm rates for in-hospital mortality prediction.

Alert fatigue remains a major barrier to the effective deployment of predictive models in emergency ...

Closed-loop and Artificial intelligence guided cardiopulmonary resuscitation using real-time physiological signals: a systematic review and meta-analysis.

BACKGROUND: Current cardiopulmonary resuscitation (CPR) includes breaks to check rhythm and pulse, w...

Unraveling the potential carcinogenic risk of bisphenols: a comprehensive network analysis and computational toxicology insights.

Dietary exposure to antimicrobial residues in eggs: Traceability-driven risk heterogeneity and national monitoring optimization in China.

Egg production is growing rapidly to meet global protein demand, but in low- and middle-income count...