Emergency Medicine

Identifying low acuity Emergency Department visits with a machine learning approach: The low acuity visit algorithms (LAVA).

OBJECTIVE: To improve the performance of International Classification of Disease (ICD) code rule-bas...

Deep learning-based quantification of total bleeding volume and its association with complications, disability, and death in patients with aneurysmal subarachnoid hemorrhage.

OBJECTIVE: The relationships between immediate bleeding severity, postoperative complications, and l...

Predicting Hydrocarbon Primary Biodegradation in Soil and Sediment Systems Using System Parameterization and Machine Learning.

Technical complexity associated with biodegradation testing, particularly for substances of unknown ...

Machine Learning Identifies Higher Survival Profile In Extracorporeal Cardiopulmonary Resuscitation.

OBJECTIVES: Extracorporeal cardiopulmonary resuscitation (ECPR) has been shown to improve neurologic...

[Orthopedics and trauma surgery in the digital age].

BACKGROUND: Digital transformation is shaping the future of orthopedics and trauma surgery. Telemedi...

New technology, psychiatry, and the law: Panic, prudence, possibility.

Throughout human history, all new technology has been met with surprise, anxiety, panic, and - event...

Artificial intelligence to advance acute and intensive care medicine.

PURPOSE OF REVIEW: This review explores recent key advancements in artificial intelligence for acute...

Enhanced skin burn assessment through transfer learning: a novel framework for human tissue analysis.

Visual inspection is the typical way for evaluating burns, due to the rising occurrence of burns glo...

Deus Ex Machina? The Rise of Artificial Intelligence in Toxicology.

Artificial intelligence (AI) is rising rapidly, driven by big data, complex algorithms, and computin...

Methodological issues on precision and prediction value of ChatGPT in emergency department triage decisions.

The AI-driven Drug Design (AIDD) platform: an interactive multi-parameter optimization system integrating molecular evolution with physiologically based pharmacokinetic simulations.

Computer-aided drug design has advanced rapidly in recent years, and multiple instances of in silico...

In Silico Prediction of Oral Acute Rodent Toxicity Using Consensus Machine Learning.

Acute oral toxicity (AOT) is required for the classification and labeling of chemicals according to ...

Early identification of suspected serious infection among patients afebrile at initial presentation using neural network models and natural language processing: A development and external validation study in the emergency department.

OBJECTIVE: To develop and externally validate models based on neural networks and natural language p...

Deep Learning during burn prehospital care: An evolving perspective.

Harnessing the Power of Generative AI for Clinical Summaries: Perspectives From Emergency Physicians.

STUDY OBJECTIVE: The workload of clinical documentation contributes to health care costs and profess...

Artificial intelligence in the diagnosis and treatment of acute appendicitis: a narrative review.

Artificial intelligence is transforming healthcare. Artificial intelligence can improve patient care...

Deciphering the Lexicon of Protein Targets: A Review on Multifaceted Drug Discovery in the Era of Artificial Intelligence.

Understanding protein sequence and structure is essential for understanding protein-protein interact...

Regenerative rehabilitation measures to restore tissue function after arsenic exposure.

Environmental exposure of arsenic impairs the cardiometabolic profile, skeletal muscle health, and n...

The future of burn management: How can machine learning lead to a revolution in improving the rehabilitation of burn patients?

Investigating the Aryl Hydrocarbon Receptor Agonist/Antagonist Conformational Switch Using Well-Tempered Metadynamics Simulations.

The aryl hydrocarbon receptor (AhR) is a ligand-dependent transcription factor that mediates biologi...

A machine learning algorithm-based predictive model for pressure injury risk in emergency patients: A prospective cohort study.

OBJECTIVES: To construct pressure injury risk prediction models for emergency patients based on diff...