Emergency Medicine

Combined robot-assisted transabdominal and perineal approach to reconstruct the posterior urethral distracted defect due to pelvic fracture: A case report.

Deep learning-assisted identification and quantification of aneurysmal subarachnoid hemorrhage in non-contrast CT scans: Development and external validation of Hybrid 2D/3D UNet.

Accurate stroke assessment and consequent favorable clinical outcomes rely on the early identificati...

A Review on the Recent Applications of Deep Learning in Predictive Drug Toxicological Studies.

Drug toxicity prediction is an important step in ensuring patient safety during drug design studies....

Artificial intelligence chatbot performance in triage of ophthalmic conditions.

BACKGROUND: Timely access to human expertise for affordable and efficient triage of ophthalmic condi...

Artificial intelligence in detecting dentomaxillofacial fractures in diagnostic imaging: a scoping review protocol.

INTRODUCTION: The dentomaxillofacial (DMF) area, which includes the teeth, maxilla, mandible, zygoma...

Real-time artificial intelligence system for bacteremia prediction in adult febrile emergency department patients.

BACKGROUND: Artificial intelligence (AI) holds significant potential to be a valuable tool in health...

Social Risk Factors are Associated with Risk for Hospitalization in Home Health Care: A Natural Language Processing Study.

OBJECTIVE: This study aimed to develop a natural language processing (NLP) system that identified so...

A Weakly Supervised Deep Learning Framework for Whole Slide Classification to Facilitate Digital Pathology in Animal Study.

The pathology of animal studies is crucial for toxicity evaluations and regulatory assessments, but ...

Neural network for autonomous segmentation and volumetric assessment of clot and edema in acute and subacute intracerebral hemorrhages.

INTRODUCTION: Minimally-invasive surgical techniques for intracerebral hemorrhage (ICH) evacuation u...

Spatial attention-based residual network for human burn identification and classification.

Diagnosing burns in humans has become critical, as early identification can save lives. The manual p...

Quality of Layperson CPR Instructions From Artificial Intelligence Voice Assistants.

An AI-Enabled Dynamic Risk Stratification for Emergency Department Patients with ECG and CXR Integration.

Emergency department (ED) triage scale determines the priority of patient care and foretells the pro...

Risk of Induction of Corneal Neovascularization with Topical Erythropoietin: An Animal Safety Study.

PURPOSE: To evaluate the pro-angiogenic effect of topical erythropoietin on cornea in chemical burn-...

Feasibility of intra-operative image guidance in burn excision surgery with multispectral imaging and deep learning.

BACKGROUND: Exposing a healthy wound bed for skin grafting is an important step during burn surgery ...

A systematic review on intracranial aneurysm and hemorrhage detection using machine learning and deep learning techniques.

The risk of discovering an intracranial aneurysm during the initial screening and follow-up screenin...

Deep Learning for Localized Detection of Optic Disc Hemorrhages.

PURPOSE: To develop an automated deep learning system for detecting the presence and location of dis...

Mechanistic Task Groupings Enhance Multitask Deep Learning of Strain-Specific Ames Mutagenicity.

The Ames test is a gold standard mutagenicity assay that utilizes various strains with and without ...

Diagnostic Test Accuracy of Deep Learning Prediction Models on COVID-19 Severity: Systematic Review and Meta-Analysis.

BACKGROUND: Deep learning (DL) prediction models hold great promise in the triage of COVID-19.

Artificial Intelligence for Detecting Acute Fractures in Patients Admitted to an Emergency Department: Real-Life Performance of Three Commercial Algorithms.

RATIONALE AND OBJECTIVES: Interpreting radiographs in emergency settings is stressful and a burden f...

Identification of key genes in spontaneous cerebral hemorrhage and prevention of disease damage: LASSO and SVM regression.

Prevention is more important than treatment, and the incidence of intracerebral hemorrhage can be ef...

Letter: Deep Neural Networks Can Accurately Detect Blood Loss and Hemorrhage Control Task Success from Video.