Emergency Medicine

Artificial intelligence CAD tools in trauma imaging: a scoping review from the American Society of Emergency Radiology (ASER) AI/ML Expert Panel.

BACKGROUND: AI/ML CAD tools can potentially improve outcomes in the high-stakes, high-volume model o...

A survey of ASER members on artificial intelligence in emergency radiology: trends, perceptions, and expectations.

PURPOSE: There is a growing body of diagnostic performance studies for emergency radiology-related a...

Incorporating algorithmic uncertainty into a clinical machine deep learning algorithm for urgent head CTs.

Machine learning (ML) algorithms to detect critical findings on head CTs may expedite patient manage...

A Patch-Based Deep Learning Approach for Detecting Rib Fractures on Frontal Radiographs in Young Children.

Chest radiography is the modality of choice for the identification of rib fractures in young childre...

Will Artificial Intelligence be Useful (or Misused) in Environmental Toxicology and Chemistry?

Emergency department use and Artificial Intelligence in Pelotas: design and baseline results.

OBJETIVO: To describe the initial baseline results of a population-based study, as well as a protoco...

External Validation of an Artificial Intelligence Device for Intracranial Hemorrhage Detection.

BACKGROUND: Artificial intelligence applications have gained traction in the field of cerebrovascula...

Artificial intelligence and machine learning disciplines with the potential to improve the nanotoxicology and nanomedicine fields: a comprehensive review.

The use of nanomaterials in medicine depends largely on nanotoxicological evaluation in order to ens...

Science fiction or clinical reality: a review of the applications of artificial intelligence along the continuum of trauma care.

Artificial intelligence (AI) and machine learning describe a broad range of algorithm types that can...

Orthopedic Robot-Assisted Femoral Neck System in the Treatment of Femoral Neck Fracture.

Cannulated screw fixation is the main therapy for femoral neck fractures, especially in young patien...

Computed tomography-based COVID-19 triage through a deep neural network using mask-weighted global average pooling.

BACKGROUND: There is an urgent need to find an effective and accurate method for triaging coronaviru...

Computed Tomography of the Head : A Systematic Review on Acquisition and Reconstruction Techniques to Reduce Radiation Dose.

In 1971, the first computed tomography (CT) scan was performed on a patient's brain. Clinical CT sys...

The association of radiologic body composition parameters with clinical outcomes in level-1 trauma patients.

PURPOSE: The present study aims to assess whether CT-derived muscle mass, muscle density, and viscer...

A Novel Mini-Invasive Technique of Arthroscopic-Assisted Reduction and Robot-Assisted Fixation for Trans-Scaphoid Perilunate Fracture Dislocations.

OBJECTIVE: Perilunate injuries are rare but devastating carpal injuries. The treatment of perilunate...

A Retrospective Study of Puncture and Drainage for Primary Brainstem Hemorrhage With the Assistance of a Surgical Robot.

BACKGROUND: Whether primary brainstem hemorrhage (PBH) should be treated with a conservative treatme...

The Environmental Conditions, Treatments, and Exposures Ontology (ECTO): connecting toxicology and exposure to human health and beyond.

BACKGROUND: Evaluating the impact of environmental exposures on organism health is a key goal of mod...

Research on Evaluation of University Emergency Management Ability Based on BP Neural Network.

University emergency management ability is an important part of university safety management. To eva...

Artificial intelligence and machine learning for hemorrhagic trauma care.

Artificial intelligence (AI), a branch of machine learning (ML) has been increasingly employed in th...

Spatial and deep learning analyses of urban recovery from the impacts of COVID-19.

This study investigates urban recovery from the COVID-19 pandemic by focusing on three main types of...

Modeling acute care utilization: practical implications for insomnia patients.

Machine learning models can help improve health care services. However, they need to be practical to...

Conventional Versus Artificial Intelligence-Assisted Interpretation of Chest Radiographs in Patients With Acute Respiratory Symptoms in Emergency Department: A Pragmatic Randomized Clinical Trial.

OBJECTIVE: It is unknown whether artificial intelligence-based computer-aided detection (AI-CAD) can...