Emergency Medicine

Identification of key therapeutic targets in nicotine-induced intracranial aneurysm through integrated bioinformatics and machine learning approaches.

BACKGROUND: Intracranial aneurysm (IA) is a critical cerebrovascular condition, and nicotine exposure is a known risk factor. This study delves into the toxicological mechanisms of nicotine in IA, aiming to identify key biomarkers and therapeutic targets.

ChatGPT-supported patient triage with voice commands in the emergency department: A prospective multicenter study.

BACKGROUND: Triage aims to prioritize patients according to their medical urgency by accurately evaluating their clinical conditions, managing waiting times efficiently, and improving the overall effectiveness of emergency care. This study aims to assess ChatGPT's performance in patient triage across four emergency departments with varying dynamics and to provide a detailed analysis of its strengt...

Comparing machine learning models for predicting preoperative DVT incidence in elderly hypertensive patients with hip fractures: a retrospective analysis.

Hip fractures in the elderly present a significant public health challenge globally, especially among patients with hypertension, who are at an increa...

Physiological and morphological impact of physical activity and nutritional interventions to offset disuse-induced skeletal muscle atrophy.

Skeletal muscle tissue acts as a functional unit for physical movements, energy metabolism, thermogenesis, and metabolic homeostasis. In this literatu...

A prediction model of pediatric bone density from plain spine radiographs using deep learning.

Osteoporosis, a bone disease characterized by decreased bone mineral density (BMD) resulting in decreased mechanical strength and an increased fractur...

Exploratory cluster analysis of IL2Ra and associated biomarkers and complications after blunt chest trauma.

BACKGROUND: Rib fractures compromise approximately 40% of all fractures in the United States. Despite their prevalence, the relationship between rib f...

Ultrasound-activated piezoelectric biomaterials for cartilage regeneration.

Due to the low density of chondrocytes and limited ability to repair damaged extracellular matrix (ECM) in cartilage, many patients with congenital or...

Risk Factors and Outcomes of Hemorrhagic Transformation in Acute Ischemic Stroke Following Thrombolysis: Analysis of a Single-Center Experience and Review of the Literature.

: This is a retrospective study conducted at the Clinical County Hospital of Craiova, Romania, providing valuable insights into hemorrhagic transforma...

Deep learning enabled liquid-based cytology model for cervical precancer and cancer detection.

Deep learning (DL) enabled liquid-based cytology has potential for cervical cancer screening or triage. Here, we develop a DL model using whole cytolo...

Toxicological evaluation of Artocarpus lacucha ethyl acetate extract: in vitro and in vivo assessment.

ETHNOPHARMACOLOGICAL RELEVANCE: Artocarpus lacucha Buch. -Ham. (syn. Artocarpus lakoocha) (A. lacucha), is a tropical fruit tree and a member of the M...

Mitochondrial toxic prediction of marine alga toxins using a predictive model based on feature coupling and ensemble learning algorithms.

Alga toxins have recently emerged as environmental risk factors to multiple human health issues. Mitochondrial toxicity is an essential element in the...

Peripheral blood immune landscape and NXPE3 as a novel biomarker for hypertensive intracerebral hemorrhage risk prediction and targeted therapy.

We employed bulk RNA-seq and scRNA-seq techniques to analyze the immune dysregulation in patients with intracerebral hemorrhage (ICH). The study revea...

Cost-Effectiveness Analysis of a Machine Learning-Based eHealth System to Predict and Reduce Emergency Department Visits and Unscheduled Hospitalizations of Older People Living at Home: Retrospective Study.

BACKGROUND: Dependent older people or those losing their autonomy are at risk of emergency hospitalization. Digital systems that monitor health remote...

Utilizing machine learning and geographic analysis to improve Post-crash traffic injury management and emergency response systems.

Traffic injuries are a major public health concern globally. This study uses machine learning (ML) and geographic analysis to analyse road traffic fat...

Bridging Data Gaps in Emergency Care: The NIGHTINGALE Project and the Future of AI in Mass Casualty Management.

In the context of mass casualty incident (MCI) management, artificial intelligence (AI) represents a promising future, offering potential improvements...

Domestic violence and childhood trauma among married women using machine learning approach: a cross-sectional study.

BACKGROUND: Globally, 27% of ever-partnered women aged 15-49 have experienced physical, sexual, or intimate partner violence at least once in their li...

The role of artificial intelligence in predicting injured structures based on clinical images of lacerations in the volar aspect of the hand and forearm.

INTRODUCTION: Recently introduced image processing capabilities of AI models, which are accessible to a broad audience, may contribute to progress in ...

Semantic-consistent diffusion model for unsupervised traumatic brain injury detection and segmentation from computed tomography images.

BACKGROUND: Unsupervised traumatic brain injury (TBI) lesion detection aims to identify and segment abnormal regions, such as cerebral edema and hemor...

AI-enhanced resuscitation image production training: advancing diversity and inclusion with GPT-4o.

Improving the usability of large emergency 911 data reporting systems: A machine learning case study using emergency incident descriptions.

INTRODUCTION: Emergency 9-1-1 incident data are recorded voluntarily within fire-department-specific computer-aided dispatch systems. The National Fir...