Emergency Medicine

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 AI identified 45 candidate genes and 21 top features (10 positive and 11 negative regulations) influencing heat stress tolerance. Heat stress is a significant threat to Brassica napus cultivation, a globally important oilseed crop for vegetable oil production. However, identifying the genes associa...

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 early pregnancy. This study investigates how laminin s...

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 found in electronic health records, with limited ...

Jigsaws soup: Improved laparoscopic surgical gesture classification, and skill level evaluation using model souping.

Laparoscopy has revolutionised surgery, with faster recovery and less trauma for patients. However, extensive training is needed to gain the required ...

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 infections cause high mortality in intensive care units (...

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 care, particularly in the context of rare but crit...

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, while high-quality CPR requires continual chest com...

Artificial intelligence in the diagnosis and prognosis of ocular trauma: a systematic review.

Dynamic demand forecasting and capacity assessment for emergency care system: a hybrid time series and machine learning approach with evidence from Beijing.

Low atherogenic index of plasma is associated with spontaneous hemorrhagic transformation in acute ischemic stroke patients: a retrospective cohort study and predictive modeling based on machine learning.

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 countries, heavy antimicrobial use, fragmented supply c...

The Future of Artificial Intelligence in Emergency Medical Services by 2030: An International Consensus Report.

OBJECTIVES: Artificial intelligence (AI) is an application of digital technology with considerable potential to improve quality, safety, and access; h...

Global distribution, pathogen spectrum, and invasion potential of Hyalomma anatolicum at the human-livestock interface: A systematic review, meta-analysis, and ecological niche modeling.

Hyalomma anatolicum is an efficient vector at the human-livestock interface, yet its global ecological profile remains insufficiently defined. This st...

Evaluating the Performance of Large Language Models for Generating Emergency Department Discharge Instructions.

BACKGROUND: Clear discharge instructions are essential for safe emergency department (ED) care, yet creating patient-centered, health literate materia...

Use of artificial intelligence and radiomics for diagnosis and prediction of osteoporotic fractures: a systematic review.

AIM: Osteoporosis (OP) is a prevalent metabolic bone disease causing millions of fractures annually, leading to significant healthcare and economic bu...

Assessing the impact of groundwater abstraction and concrete dam fractures on saltwater intrusion using numerical modeling and interpretable machine learning.

Reliable prediction of SWI is essential for protecting coastal groundwater. In this study, the SWI wedge length in a sloping coastal aquifer controlle...

Accurate, fair, and generalisable scaling of injury severity score-based AI with demographics in terms of mortality in patients with trauma: multi-centre, multi-national retrospective cohort study.

BACKGROUND: Accurate and equitable prediction of trauma-related in-hospital mortality is critical for guiding clinical decisions and optimising trauma...

Acid-Base Status During Venoarterial Extracorporeal Membrane Oxygenator Support in Patients With Cardiogenic Shock.

BACKGROUND: The prognostic significance of an adverse acid-base milieu despite venoarterial extracorporeal membrane oxygenation support in patients wi...