Emergency Medicine

Designing and executing a functional exercise to test a novel informatics tool for mass casualty triage.

OBJECTIVE: The testing of informatics tools designed for use during mass casualty incidents presents...

[Robotic-assisted supraomohyoid neck dissection via retroauricular hairline incision].

To explore the feasibility of using da Vinci Surgical System to perform supraomohyoid neck dissecti...

A Double-Blind, Randomized Control Trial of Rapidly Infused High Strong Ion Difference (SID) Fluid Versus Hartmann's Solution on Acid-Base Status in Sepsis Patients in the Emergency Department.

BACKGROUND: Balanced fluids are preferred in initial resuscitation of septic patients based on sever...

Bundled Care for Hip Fractures: A Machine-Learning Approach to an Untenable Patient-Specific Payment Model.

OBJECTIVES: With the transition to a value-based model of care delivery, bundled payment models have...

Artificial neural networks can predict trauma volume and acuity regardless of center size and geography: A multicenter study.

BACKGROUND: Trauma has long been considered unpredictable. Artificial neural networks (ANN) have rec...

Comparison of Machine Learning Optimal Classification Trees With the Pediatric Emergency Care Applied Research Network Head Trauma Decision Rules.

IMPORTANCE: Computed tomographic (CT) scanning is the standard for the rapid diagnosis of intracrani...

Training and Interpreting Machine Learning Algorithms to Evaluate Fall Risk After Emergency Department Visits.

BACKGROUND: Machine learning is increasingly used for risk stratification in health care. Achieving ...

A Robust Machine Learning Architecture for a Reliable ECG Rhythm Analysis during CPR.

Chest compressions delivered during cardiopulmonary resuscitation (CPR) induce artifacts in the ECG ...

1D Convolutional Neural Networks for Estimation of Compensatory Reserve from Blood Pressure Waveforms.

We propose a Deep Convolutional Neural Network (CNN) architecture for computing a Compensatory Reser...

Improving Sensitivity on Identification and Delineation of Intracranial Hemorrhage Lesion Using Cascaded Deep Learning Models.

Highly accurate detection of the intracranial hemorrhage without delay is a critical clinical issue ...

Combining Natural Language Processing of Electronic Medical Notes With Administrative Data to Determine Racial/Ethnic Differences in the Disclosure and Documentation of Military Sexual Trauma in Veterans.

BACKGROUND: Despite national screening efforts, military sexual trauma (MST) is underreported. Littl...

A Systems Toxicology Approach for the Prediction of Kidney Toxicity and Its Mechanisms In Vitro.

The failure to predict kidney toxicity of new chemical entities early in the development process bef...

Opportunities and challenges using artificial intelligence in ADME/Tox.

A recent conference organized a panel of scientists representing small and big pharma companies, who...

Burn wound classification model using spatial frequency-domain imaging and machine learning.

Accurate assessment of burn severity is critical for wound care and the course of treatment. Delays ...

Natural language processing and machine learning to identify alcohol misuse from the electronic health record in trauma patients: development and internal validation.

OBJECTIVE: Alcohol misuse is present in over a quarter of trauma patients. Information in the clinic...

Continuous Glucose Monitoring Linked to an Artificial Intelligence Risk Index: Early Footprints of Intraventricular Hemorrhage in Preterm Neonates.

OBJECTIVE: To develop and validate a new risk score for intraventricular hemorrhage (IVH) in preterm...

Heart rate variability based machine learning models for risk prediction of suspected sepsis patients in the emergency department.

Early identification of high-risk septic patients in the emergency department (ED) may guide appropr...

Recent Advances in Machine Learning Methods for Predicting Heat Shock Proteins.

BACKGROUND: As molecular chaperones, Heat Shock Proteins (HSPs) not only play key roles in protein f...

Oy Vey! A Comment on "Machine Learning of Toxicological Big Data Enables Read-Across Structure Activity Relationships Outperforming Animal Test Reproducibility".

Automatic hip geometric feature extraction in DXA imaging using regional random forest.

BACKGROUND: Hip fracture is considered one of the salient disability factors across the global popul...

Building deep learning models for evidence classification from the open access biomedical literature.

We investigate the application of deep learning to biocuration tasks that involve classification of ...