Emergency Medicine

Fundus images analysis using deep features for detection of exudates, hemorrhages and microaneurysms.

BACKGROUND: Convolution neural networks have been considered for automatic analysis of fundus images to detect signs of diabetic retinopathy but suffer from low sensitivity.

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 states. Mitochondrial image analysis is typically done on still images using slow manual methods or automated methods of limited types of features. MitoMo integrated software overcomes these bottlenecks by automating rapid unbiased quantitative analysis of mitochondrial morphology, texture, motion, ...

A Randomized Control Trial Of Anti-Inflammatory Regional Hypothermia On Urinary Continence During Robot-Assisted Radical Prostatectomy.

The present study seeks to present a single-blind, randomized control trial of a hypothermic anti-inflammatory device, the endorectal cooling balloon ...

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 management a growing public health problem. Biopsy and...

Using an artificial neural network to predict traumatic brain injury.

In BriefPediatric traumatic brain injury (TBI) is common, but not all injuries require hospitalization. A computational tool for ruling-in patients wh...

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 and detection of multiple bacterial pathogens magne...

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 contribute to improve therapy and increase cardia...

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. Inexpensive and accurate person-level assessment of ...

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 diverse, but one of the key factors is the time for ...

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 many overdoses and deaths worldwide. Furanylfentan...

Deep neural network improves fracture detection by clinicians.

Suspected fractures are among the most common reasons for patients to visit emergency departments (EDs), and X-ray imaging is the primary diagnostic t...

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 of neonatal self-inflating bags (SIB) compliant wit...

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 detect venous thromboembolism (VTE) in the acute ph...

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 emergency department (ED) overcrowding has become a na...

Deep learning algorithms for detection of critical findings in head CT scans: a retrospective study.

BACKGROUND: Non-contrast head CT scan is the current standard for initial imaging of patients with head trauma or stroke symptoms. We aimed to develop...

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 measurement of bone mineral density (BMD) in reliable...

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 weight-based fluconazole dosing on liver injury is ...

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 because no analytic objective functions are availab...

Artificial Intelligence Applied to Osteoporosis: A Performance Comparison of Machine Learning Algorithms in Predicting Fragility Fractures From MRI Data.

BACKGROUND: A current challenge in osteoporosis is identifying patients at risk of bone fracture.