Emergency Medicine

Machine learning improves prediction of delayed cerebral ischemia in patients with subarachnoid hemorrhage.

BACKGROUND AND PURPOSE: Delayed cerebral ischemia (DCI) is a severe complication in patients with an...

Defining heatwave thresholds using an inductive machine learning approach.

Establishing appropriate heatwave thresholds is important in reducing adverse human health consequen...

Deep Analysis of Mitochondria and Cell Health Using Machine Learning.

There is a critical need for better analytical methods to study mitochondria in normal and diseased ...

Machine learning to predict lung nodule biopsy method using CT image features: A pilot study.

Computed tomography (CT)-based screening on lung cancer mortality is poised to make lung nodule mana...

Antimicrobial peptide based magnetic recognition elements and Au@Ag-GO SERS tags with stable internal standards: a three in one biosensor for isolation, discrimination and killing of multiple bacteria in whole blood.

In this study, a new biosensor based on a sandwich structure has been developed for the isolation an...

A Machine Learning Shock Decision Algorithm for Use During Piston-Driven Chest Compressions.

GOAL: Accurate shock decision methods during piston-driven cardiopulmonary resuscitation (CPR) would...

Ensemble machine learning prediction of posttraumatic stress disorder screening status after emergency room hospitalization.

Posttraumatic stress disorder (PTSD) develops in a substantial minority of emergency room admits. In...

A data-driven artificial intelligence model for remote triage in the prehospital environment.

In a mass casualty incident, the factors that determine the survival rate of injured patients are di...

A GC-MS method for the determination of furanylfentanyl and ocfentanil in whole blood with full validation.

PURPOSE: Fentanyl analogues are popular in recent years among drug addicts and have been related to ...

Deep neural network improves fracture detection by clinicians.

Suspected fractures are among the most common reasons for patients to visit emergency departments (E...

Machine Learning for Environmental Toxicology: A Call for Integration and Innovation.

Newborn self-inflating manual resuscitators: precision robotic testing of safety and reliability.

AIM: A controlled bench test was undertaken to determine the performance variability among a range o...

Novel screening criteria for post-traumatic venous thromboembolism by using D-dimer.

AIM: Because severe trauma patients frequently manifest coagulopathy, it is extremely important to d...

Validation of deep-learning-based triage and acuity score using a large national dataset.

AIM: Triage is important in identifying high-risk patients amongst many less urgent patients as emer...

FRAX Calculated without BMD Resulting in a Higher Fracture Risk Than That Calculated with BMD in Women with Early Breast Cancer.

BACKGROUND AND PURPOSE: The aim of this study was to investigate the importance of including the mea...

Critically Ill Recipients of Weight-Based Fluconazole Meeting Drug-Induced Liver Injury Network Criteria.

Fluconazole-associated liver injury is estimated to occur in <10% of patients; however, effect of w...

A Random Forest-Assisted Evolutionary Algorithm for Data-Driven Constrained Multiobjective Combinatorial Optimization of Trauma Systems.

Many real-world optimization problems can be solved by using the data-driven approach only, simply b...

Simulating exposure-related behaviors using agent-based models embedded with needs-based artificial intelligence.

Exposure to a chemical is a critical consideration in the assessment of risk, as it adds real-world ...

Deep Learning in Drug Discovery and Medicine; Scratching the Surface.

The practice of medicine is ever evolving. Diagnosing disease, which is often the first step in a cu...

The Impact of Health Equity Coaching on Patient's Perceptions of Cultural Competency and Communication in a Pediatric Emergency Department: An Intervention Design.

PURPOSE: American Indian (AI) children experience significant disparities in health-care access. As ...

Improving the Accuracy of Scores to Predict Gastrostomy after Intracerebral Hemorrhage with Machine Learning.

BACKGROUND: Gastrostomy placement after intracerebral hemorrhage indicates the need for continued me...