Emergency Medicine

Cross-validation of an artificial intelligence tool for fracture classification and localization on conventional radiography in Dutch population.

OBJECTIVES: The aim of this study is to validate the effectiveness of an AI tool trained on Indian data in a Dutch medical center and to assess its ability to classify and localize fractures.

Predicting Unplanned Intubations in Rib Fracture Patients: An Interpretable Machine Learning Approach.

BackgroundTraumatic rib fractures can lead to respiratory complications necessitating unplanned intubation, but predictors have been inadequately delineated. We used interpretable machine learning to predict unplanned intubations in rib fracture patients while identifying predictors.MethodsTQIP 2017-2022 was queried for adult patients admitted to the hospital following a rib fracture injury. An XG...

Clinical decision support using pseudo-notes from multiple streams of EHR data.

Electronic health records (EHR) contain data from disparate sources, spanning various biological and temporal scales. In this work, we introduce the M...

Spatial analysis of county-level determinants of overdose mortality in the United States using spatial machine learning.

In recent years, there has been a growing body of literature on identifying effective determinants for modeling the spatial variation of overdose rate...

Development and validation of a transformer model-based early warning score for real-time prediction of adverse outcomes in the emergency department.

This study aimed to develop and validate a transformer-based early warning score (TEWS) system for predicting adverse events (AEs) in the emergency de...

Parsimonious and explainable machine learning for predicting mortality in patients post hip fracture surgery.

Hip fractures among the elderly population continue to present significant risks and high mortality rates despite advancements in surgical procedures....

Clinical validation of AI assisted animal ultrasound models for diagnosis of early liver trauma.

The study aimed to develop an AI-assisted ultrasound model for early liver trauma identification, using data from Bama miniature pigs and patients in ...

AI in Learning Anatomy and Restoring Central Incisors: A Comparative Study.

More than 1 billion individuals worldwide have experienced dental trauma, particularly children aged 7 to 12 y, predominantly affecting the anterior t...

Natural orifice transluminal endoscopic surgery: history and current development.

Natural orifice transluminal endoscopic surgery (NOTES) represents an innovative advancement in minimally invasive surgery, utilizing natural body ori...

Harnessing AI for Improved Diagnosis and Management of Pediatric Sepsis: Current Advances, Challenges, and Future Directions.

Artificial intelligence (AI) has been applied to early recognition and management of rapidly progressive, community-acquired pediatric sepsis, a leadi...

Identifying real time surveillance indicators to estimate COVID-19 hospital admissions in Colorado during and after the public health emergency.

Questions remain about how best to focus surveillance efforts for COVID-19 and other emerging respiratory diseases. We used an archive of COVID-19 dat...

Machine learning to improve predictive performance of prehospital early warning scores.

Early warning scores are used to assess acute patients' risk of being in a critical situation, allowing for early appropriate treatment, avoiding crit...

Optimization of the heat recovery performance of enhanced geothermal system based on PSO-GA-BP neural networks and analytic hierarchy process.

Numerical simulation is the most commonly used method to predict the power generation capacity of EGS during geothermal energy extraction. However, it...

Automatic pain classification in older patients with hip fracture based on multimodal information fusion.

Given the limitations of unimodal pain recognition approaches, this study aimed to develop a multimodal pain recognition system for older patients wit...

Machine learning and transformer models for prediction of postoperative pneumonia risk in patients with lower limb fractures.

Postoperative pneumonia, a prevalent complication arising from lower limb fracture surgery, can significantly prolong hospitalization periods and elev...

Assessment of spatial autocorrelation and scalability in fine-scale wildfire random forest prediction models.

Wildfire prediction models that can be applied across diverse regions at fine scales (< 100 m) are critical for wildfire management. Remote sensing of...

Formulation of low temperature mixed mode crack propagation behavior of crumb rubber modified HMA using artificial intelligence.

Determining mixed mode fracture parameters asphalt concrete mixtures remains an engineering challenge due to non-homogeneity and inelasticity of the m...

Automatic recognition and differentiation of pulmonary contusion and bacterial pneumonia based on deep learning and radiomics.

BACKGROUND: In clinical work, there are difficulties in distinguishing pulmonary contusion(PC) from bacterial pneumonia(BP) on CT images by the naked ...

Comparison of AI-generated and clinician-designed multiple-choice questions in emergency medicine exam: a psychometric analysis.

BACKGROUND: Artificial intelligence (AI) has shown promise in generating multiple-choice questions (MCQs) for medical education, yet the psychometric ...

Enhancing out-of-hospital cardiac arrest survival in China through the 5-minute social rescue circle implementation.

BACKGROUND: Out-of-hospital cardiac arrest (OHCA) survival in China remains critically low due to limited bystander cardiopulmonary resuscitation (CPR...