Emergency Medicine

Comprehensive Management of Intracranial Aneurysms Using Artificial Intelligence: An Overview.

Intracranial aneurysms (IAs), an asymptomatic vascular lesion, are becoming increasingly common as imaging technology progresses. Subarachnoid hemorrhage from IAs rupture entails a substantial risk of mortality or severe disability. The early detection and prompt intervention of IAs posing a high risk of rupture are paramount for optimizing clinical management and safeguarding patients' lives. Art...

Predicting Epidural Hematoma Expansion in Traumatic Brain Injury: A Machine Learning Approach.

IntroductionTraumatic brain injury (TBI) is a leading cause of disability and mortality worldwide, with epidural hematoma (EDH) being a severe consequence. This study focuses on identifying factors predicting EDH volume changes in TBI patients and developing a machine learning (ML) model to predict EDH expansion.MethodsThe study includes patients with traumatic EDH between 2019 and 2021. Data were...

Development of an Artificial Intelligence-Based Algorithm for the Assessment of Skeletal Age and Detection of Cervical Vertebral Anomalies in Patients with Cleft Lip and Palate.

ObjectiveTo develop an artificial intelligence (AI)-based algorithm for the assessment and comparison of skeletal maturation in patients with and with...

Utilizing integrated bioinformatics and machine learning approaches to elucidate biomarkers linking sepsis to fatty acid metabolism-associated genes.

Sepsis, characterized as a systemic inflammatory response triggered by the invasion of pathogens, represents a continuum that may escalate from mild s...

Using large language models (ChatGPT, Copilot, PaLM, Bard, and Gemini) in Gross Anatomy course: Comparative analysis.

The increasing application of generative artificial intelligence large language models (LLMs) in various fields, including medical education, raises q...

A digital phenotyping dataset for impending panic symptoms: a prospective longitudinal study.

This study investigated the utilization of digital phenotypes and machine learning algorithms to predict impending panic symptoms in patients with moo...

Development of a simplified model and nomogram for the prediction of pulmonary hemorrhage in respiratory distress syndrome in extremely preterm infants.

BACKGROUND: Pulmonary hemorrhage (PH) in respiratory distress syndrome (RDS) in extremely preterm infants exhibits a high mortality rate and poor long...

Prioritization of monitoring compounds from SNTS identified organic micropollutants in contaminated groundwater using a machine learning optimized ToxPi model.

Advanced suspect and non-target screening (SNTS) approach can identify a large number of potential hazardous micropollutants in groundwater, underscor...

An AI deep learning algorithm for detecting pulmonary nodules on ultra-low-dose CT in an emergency setting: a reader study.

BACKGROUND: To retrospectively assess the added value of an artificial intelligence (AI) algorithm for detecting pulmonary nodules on ultra-low-dose c...

Machine Learning Algorithms Exceed Comorbidity Indices in Prediction of Short-Term Complications After Hip Fracture Surgery.

BACKGROUND: Hip fractures are among the most morbid acute orthopaedic injuries often due to accompanying patient frailty. The purpose of this study wa...

Machine learning outperforms the Canadian Triage and Acuity Scale (CTAS) in predicting need for early critical care.

STUDY OBJECTIVE: This study investigates the potential to improve emergency department (ED) triage using machine learning models by comparing their pr...

Aneurysmal formation of periventricular anastomosis is associated with collateral development of Moyamoya disease and its rupture portends poor prognosis: detailed analysis by multivariate statistical and machine learning approaches.

Periventricular anastomosis (PA) is the characteristic collateral network in Moyamoya disease (MMD). However, PA aneurysms are rare, resulting in limi...

Computer tomography-based radiomics combined with machine learning for predicting the time since onset of epidural hematoma.

Estimation of the age of epidural hematoma (EDH) is a challenge in clinical forensic medicine, and this issue has yet to be conclusively resolved. The...

Application and Prospects of Deep Learning Technology in Fracture Diagnosis.

Artificial intelligence (AI) is an interdisciplinary field that combines computer technology, mathematics, and several other fields. Recently, with th...

Deep learning-based automatic bleeding recognition during liver resection in laparoscopic hepatectomy.

BACKGROUND: Intraoperative hemorrhage during laparoscopic hepatectomy (LH) is a risk factor for negative postoperative outcomes. Ensuring appropriate ...

Comparative efficacy of anteroposterior and lateral X-ray based deep learning in the detection of osteoporotic vertebral compression fracture.

Magnetic resonance imaging remains the gold standard for diagnosing osteoporotic vertebral compression fractures (OVCF), but the use of X-ray imaging,...

Improving triage performance in emergency departments using machine learning and natural language processing: a systematic review.

BACKGROUND: In Emergency Departments (EDs), triage is crucial for determining patient severity and prioritizing care, typically using the Manchester T...

Application of artificial intelligence in triage in emergencies and disasters: a systematic review.

INTRODUCTION AND OBJECTIVE: Modern and intelligent triage systems are used today due to the growing trend of disasters and emergencies worldwide and t...

ResNet-Transformer deep learning model-aided detection of dens evaginatus.

BACKGROUND: Dens evaginatus is a dental morphological developmental anomaly. Failing to detect it may lead to tubercles fracture and pulpal/periapical...

Applications of artificial intelligence for chemical analysis and monitoring of pharmaceutical and personal care products in water and wastewater: A review.

Specifying and interpreting the occurrence of emerging pollutants is essential for assessing treatment processes and plants, conducting wastewater-bas...