Emergency Medicine

Personalizing anesthetic management in trauma patients using machine learning.

PURPOSE OF THE REVIEW: Artificial intelligence in health is evolving rapidly, and there is a lot of hope that it may improve patient outcomes. The perioperative management of patients with major trauma is a challenge, as it requires rapid decision-making in complex and evolving clinical situations. Anesthesiologists are central to the early resuscitation, operative management, and postoperative su...

Does Sequential Use of Multiple Chatbots Influence Emergency Guidance for Dental Avulsion?

BACKGROUND/AIM: Artificial intelligence-based chatbot systems are increasingly used for dental emergency guidance, yet the clinical value of sequential consultation remains unclear. This study investigated whether response order influences the quality of chatbot-generated answers to permanent tooth avulsion questions. MATERIAL AND METHODS: Eight frequently asked questions covering key decision poi...

GAN-GA: A Deep-Evolutionary Approach for Synthesizing Functionally Similar Heat Shock Proteins.

De novo protein design has emerged as a transformative approach for generating functional proteins without relying on naturally occurring templates, o...

Integrating AI Into Governmental Public Health Decision Making: Challenges, Considerations, and a Path Forward.

Public health emergencies such as pandemics, natural disasters, and epidemics may require rapid, high-stakes decisions often made by elected officials...

The role of large language models in the diagnosis and management of obstetric patients: a pilot feasibility study using simulated obstetric cases.

OBJECTIVE: This feasibility study aimed to assess the potential of freely available large language models (LLMs) to support clinical decision-making i...

Artificial intelligence for detecting acute heart failure on chest CT: prospective clinical proof-of-concept validation.

OBJECTIVE: Acute heart failure (AHF) is a common but underrecognized cause of dyspnea. Chest computed tomography (CT) can accurately assess pulmonary ...

AI-assisted versus fully automated volumetry for hemorrhage quantification in spontaneous ICH with ventricular extension: A multi-center study.

BACKGROUND: Spontaneous intracerebral hemorrhage (sICH) with intraventricular hemorrhage (IVH) extension is a neurological emergency associated with h...

Machine Learning-Guided Optimization of Additively Manufactured TiB2-Modified Aluminum Alloys.

The rapid development of additive manufacturing (AM) offers unprecedented design freedom for high-performance aluminum alloys, yet process optimizatio...

Tech That Scales: A Practical Framework for Artificial Intelligence-Enabled Cancer Care in Low- and Middle-Income Countries and Underserved US Counties.

Cancer outcomes remain starkly unequal: 5-year survival rates for common malignancies in low- and middle-income countries (LMICs) often lag 20-40 perc...

Integrating network toxicology and experimental validation to elucidate the molecular mechanism basis of chondrotoxicity of Benzo[a]pyrene in osteoarthritis.

Benzo[a]pyrene (BaP), a widespread environmental pollutant, has been increasingly implicated in the pathogenesis of chronic degenerative diseases. Env...

Uncovering the Global Burden and Future Trajectories of Nanomagnetite Particle Emissions from Biomass Power Plants.

Biomass power plants (BPPs) are expanding rapidly, yet the most toxicologically potent nanoscale fraction of its particulate emissions remains poorly ...

Clinician interaction with a machine learning algorithm for the assessment of patients with possible acute heart failure: a qualitative study.

BACKGROUND: Machine learning (ML) could improve clinical decisions in patients with possible acute heart failure, but few studies have evaluated accep...

Preliminary development of a child physical abuse algorithm using emergency department records.

BACKGROUND: Victims of child physical abuse (CPA) disproportionately use the emergency department, yet identifying CPA remains challenging in this set...

Automated estimation of drain output in postoperative patients using deep learning on clinical images.

Postoperative drains are essential components of care in general surgery and intensive care units, where accurate monitoring of drain output is critic...

Graph theory reveals functional connectome disruptions in adolescent major depressive disorder with childhood trauma.

BACKGROUND: Childhood trauma (CT) is a major risk factor for adolescent major depressive disorder (MDD), yet its neurobiological underpinnings and lon...

Mechanism exploration of di(2-ethylhexyl) phthalate (DEHP)-induced hepatocellular carcinoma via network toxicology and molecular docking analysis.

Chemical contaminants and fish: implications for health and ecosystem sustainability.

Chemical pollutants in aquatic ecosystems pose a significant and growing threat to fish health and overall ecosystem sustainability. This review highl...

Comparative performance of manual triage systems and ML models in predicting clinical outcomes among patients transported to the emergency department by emergency medical services.

Reconstruction of Under-Sampled Images and Concurrent Optimization of Sampling Masks for 3D Carotid Simultaneous Non-Contrast Angiography and intraPlaque Hemorrhage MRI With Model Based Deep Learning Architecture (deepSNAP).

PURPOSE: To improve the imaging efficiency of 3D carotid simultaneous noncontrast angiography and intraplaque hemorrhage (SNAP) MRI by reconstruction ...

Context-Guided Mixture-of-Experts with Multimodal LLMs for Lesion Detection in Buccal Mucosa Images.

INTRODUCTION AND AIMS: Oral lesions are highly prevalent globally, and oral cancer ranks among the most common malignancies, underscoring the need for...