Emergency Medicine

Opportunities and Challenges for Large Language Models in Primary Health Care.

Primary Health Care (PHC) is the cornerstone of the global health care system and the primary objective for achieving universal health coverage. China's PHC system faces several challenges, including uneven distribution of medical resources, a lack of qualified primary healthcare personnel, an ineffective implementation of the hierarchical medical treatment, and a serious situation regarding the p...

Prognostic assessment of osteolytic lesions and mechanical properties of bones bearing breast cancer using neural network and finite element analysis.

The management of skeletal-related events (SREs), particularly the prevention of pathological fractures, is crucial for cancer patients. Current clinical assessment of fracture risk is mostly based on medical images, but incorporating sequential images in the assessment remains challenging. This study addressed this issue by leveraging a comprehensive dataset consisting of 260 longitudinal micro-c...

Evaluating the predictive performance of different data sources to forecast overdose deaths at the neighborhood level with machine learning in Rhode Island.

OBJECTIVES: To evaluate the predictive performance of different data sources to forecast fatal overdose in Rhode Island neighborhoods, with the goal o...

Prognostic value of SAPS II score for 28-day mortality in ICU patients with acute pulmonary embolism.

BACKGROUND: Acute pulmonary embolism (APE) is a common and life-threatening emergency in intensive care units (ICUs). Effective risk assessment tools ...

Analyzing resuscitation conference content through the lens of the chain of survival.

BACKGROUND: Resuscitation science today often focuses on advanced topics such as extracorporeal cardiopulmonary resuscitation or targeted temperature ...

Developing a high-performance AI model for spontaneous intracerebral hemorrhage mortality prediction using machine learning in ICU settings.

BACKGROUND: Spontaneous intracerebral hemorrhage (SICH) is a devastating condition that significantly contributes to high mortality rates. This study ...

Machine learning-driven prediction of hospital admissions using gradient boosting and GPT-2.

BACKGROUND: Accurately predicting hospital admissions from the emergency department (ED) is essential for improving patient care and resource allocati...

Evaluating a large language model's accuracy in chest X-ray interpretation for acute thoracic conditions.

BACKGROUND: The rapid advancement of artificial intelligence (AI) has great ability to impact healthcare. Chest X-rays are essential for diagnosing ac...

Development and validation of inpatient mortality prediction models for patients with hyperglycemic crisis using machine learning approaches.

BACKGROUND: Hyperglycemic crisis is one of the most common and severe complications of diabetes mellitus, associated with a high motarlity rate. Emerg...

Constructing an early warning model for elderly sepsis patients based on machine learning.

Sepsis is a serious threat to human life. Early prediction of high-risk populations for sepsis is necessary especially in elderly patients. Artificial...

Fall recognition using a three stream spatio temporal GCN model with adaptive feature aggregation.

The prevention of falls is paramount in modern healthcare, particularly for the elderly, as falls can lead to severe injuries or even fatalities. Addi...

Evaluating multimodal ChatGPT for emergency decision-making of ocular trauma cases.

PURPOSE: This study aimed to evaluate the potential of ChatGPT in diagnosing ocular trauma cases in emergency settings and determining the necessity f...

Predicting hemorrhagic transformation in acute ischemic stroke: a systematic review, meta-analysis, and methodological quality assessment of CT/MRI-based deep learning and radiomics models.

Acute ischemic stroke (AIS) is a major cause of mortality and morbidity, with hemorrhagic transformation (HT) as a severe complication. Accurate predi...

Modelling fourth-order hyperelasticity in soft solids using physics informed neural networks without labelled data.

Mild traumatic brain injury can result from shear shock wave formation in the brain in the event of a head impact like in contact sports, road traffic...

Integrating bioinformatics and machine learning for comprehensive analysis and validation of diagnostic biomarkers and immune cell infiltration characteristics in pediatric septic shock.

This study aims to predict and diagnose pediatric septic shock through the screening of immune infiltration-related biomarkers. Three gene expression ...

Preliminary evaluation of ChatGPT model iterations in emergency department diagnostics.

Large language model chatbots such as ChatGPT have shown the potential in assisting health professionals in emergency departments (EDs). However, the ...

Artificial Intelligence and Qualitative Analysis of Emergency Department Telemental Health Care Implementation Survey.

: Implementation of telemental health care in emergency departments (EDs) in the United States (U.S.) has been increasing. Artificial intelligence (AI...

Can AI reveal the next generation of high-impact bone genomics targets?

Genetic studies have revealed hundreds of loci associated with bone-related phenotypes, including bone mineral density (BMD) and fracture risk. Howeve...

Early prediction of intraventricular hemorrhage in very low birth weight infants using deep neural networks with attention in low-resource settings.

Early prediction of intraventricular hemorrhage (IVH) in very low-birthweight infants (VLBWIs) remains challenging because of multifactorial risk fact...

Mitigation of the toxic effects of nitrite: Role and mechanism of isoleucine in mitigating mitochondrial DNA leakage-induced inflammation in grass carp (Ctenopharyngodon idella) under nitrite exposure.

The physiological and growth processes of fish are closely associated with their surrounding environment. This study investigated the role and underly...