Emergency Medicine

Identification of Patients with Nontraumatic Intracranial Hemorrhage Using Administrative Claims Data.

INTRODUCTION: Nontraumatic intracranial hemorrhage (ICH) is a neurological emergency of research int...

Anaerobic condition induces a viable but nonculturable state of the PCB-degrading Bacteria Rhodococcus biphenylivorans TG9.

Significant microbial removal of highly chlorinated polychlorinated biphenyls (PCBs) requires the co...

Computer-Aided Fracture Size Measurement in Orbital Fractures-An Alternative to Manual Evaluation.

OBJECTIVE: We aimed to present a novel semiautomated tool for orbital fracture size measurement and ...

Predicting defibrillation success in out-of-hospital cardiac arrested patients: Moving beyond feature design.

OBJECTIVE: Optimizing timing of defibrillation by evaluating the likelihood of a successful outcome ...

Exploring the Intersection between Social Determinants of Health and Unmet Dental Care Needs Using Deep Learning.

The goals of this study were to develop a risk prediction model in unmet dental care needs and to ex...

Cleaning Up the MESS: Can Machine Learning Be Used to Predict Lower Extremity Amputation after Trauma-Associated Arterial Injury?

BACKGROUND: Thirty years after the Mangled Extremity Severity Score was developed, advances in vascu...

Artificial intelligence interventions focused on opioid use disorders: A review of the gray literature.

BACKGROUND: With the artificial intelligence (AI) paradigm shift comes momentum toward the developme...

Lignin-Incorporated Nanogel Serving As an Antioxidant Biomaterial for Wound Healing.

Oxidative phosphorylation is an important biological process in the body to produce energy, during w...

Accurate and Efficient Intracranial Hemorrhage Detection and Subtype Classification in 3D CT Scans with Convolutional and Long Short-Term Memory Neural Networks.

In this paper, we present our system for the RSNA Intracranial Hemorrhage Detection challenge, which...

Machine learning prediction of the adverse outcome for nontraumatic subarachnoid hemorrhage patients.

OBJECTIVE: Subarachnoid hemorrhage (SAH) is often devastating with increased early mortality, partic...

3D Deep Neural Network Segmentation of Intracerebral Hemorrhage: Development and Validation for Clinical Trials.

Intracranial hemorrhage (ICH) occurs when a blood vessel ruptures in the brain. This leads to signif...

THEIA™ development, and testing of artificial intelligence-based primary triage of diabetic retinopathy screening images in New Zealand.

AIM: To develop and evaluate an artificial intelligence triage system with high sensitivity for dete...

Federated Gradient Averaging for Multi-Site Training with Momentum-Based Optimizers.

Multi-site training methods for artificial neural networks are of particular interest to the medical...

Deep learning-enabled analysis reveals distinct neuronal phenotypes induced by aging and cold-shock.

BACKGROUND: Access to quantitative information is crucial to obtain a deeper understanding of biolog...

Identifying Heat Shock Protein Families from Imbalanced Data by Using Combined Features.

Heat shock proteins (HSPs) are ubiquitous in living organisms. HSPs are an essential component for c...

Deep learning-based triage and analysis of lesion burden for COVID-19: a retrospective study with external validation.

BACKGROUND: Prompt identification of patients suspected to have COVID-19 is crucial for disease cont...

CT scan AI-aided triage for patients with COVID-19 in China.

An East Coast Perspective on Artificial Intelligence and Machine Learning: Part 1: Hemorrhagic Stroke Imaging and Triage.

Hemorrhagic stroke is a medical emergency. Artificial intelligence techniques and algorithms may be ...

Point-of-Care Ultrasound.

PURPOSE OF THE REVIEW: Point-of-care ultrasound using small ultrasound devices has expanded beyond e...

Biomedical document triage using a hierarchical attention-based capsule network.

BACKGROUND: Biomedical document triage is the foundation of biomedical information extraction, which...

Sanders classification of calcaneal fractures in CT images with deep learning and differential data augmentation techniques.

BACKGROUND: Classification of the type of calcaneal fracture on CT images is essential in driving tr...