Emergency Medicine

New-Onset Transient Global Amnesia: A Clinical Challenge in an Air Medical Transportation Pilot With a History of Coronavirus Disease 2019.

A 43-year-old male Bell 214C helicopter pilot presented to the emergency ward with flu-like syndrome. His nasopharyngeal severe acute respiratory syndrome coronavirus 2 real-time polymerase chain reaction test was positive, and a chest computed tomographic scan confirmed coronavirus disease 2019 pneumonia. He was admitted, received treatment, was discharged, and returned to flying. During the miss...

Comparison of state-of-the-art machine and deep learning algorithms to classify proximal humeral fractures using radiology text.

INTRODUCTION: Proximal humeral fractures account for a significant proportion of all fractures. Detailed accurate classification of the type and severity of the fracture is a key component of clinical decision making, treatment and plays an important role in orthopaedic trauma research. This research aimed to assess the performance of Machine Learning (ML) multiclass classification algorithms to c...

A pediatric wrist trauma X-ray dataset (GRAZPEDWRI-DX) for machine learning.

Digital radiography is widely available and the standard modality in trauma imaging, often enabling to diagnose pediatric wrist fractures. However, im...

An image classification deep-learning algorithm for shrapnel detection from ultrasound images.

Ultrasound imaging is essential for non-invasively diagnosing injuries where advanced diagnostics may not be possible. However, image interpretation r...

Influence of artificial intelligence on the work design of emergency department clinicians a systematic literature review.

OBJECTIVE: This systematic literature review aims to demonstrate how Artificial Intelligence (AI) is currently used in emergency departments (ED) and ...

Deep learning of birth-related infant clavicle fractures: a potential virtual consultant for fracture dating.

BACKGROUND: In infant abuse investigations, dating of skeletal injuries from radiographs is desirable to reach a clear timeline of traumatic events. P...

Expert surgeons and deep learning models can predict the outcome of surgical hemorrhage from 1 min of video.

Major vascular injury resulting in uncontrolled bleeding is a catastrophic and often fatal complication of minimally invasive surgery. At the outset o...

[The role of bile acid measurement in the management of intrahepatic cholestasis of pregnancy].

Introduction: Intrahepatic cholestasis of pregnancy complicates 1% of pregnancies. It increases the risk of severe fetal complications significantly, ...

Performance enhancement of an uncertain nonlinear medical robot with optimal nonlinear robust controller.

Cardiopulmonary resuscitation refers to the process of sending oxygen and blood to the body's vital organs during cardiac arrest. For this reason, des...

Parental Perceptions on Use of Artificial Intelligence in Pediatric Acute Care.

BACKGROUND: Family engagement is critical in the implementation of artificial intelligence (AI)-based clinical decision support tools, which will play...

Exemplar deep and hand-modeled features based automated and accurate cerebral hemorrhage classification method.

BACKGROUND: Cerebral hemorrhage (CH) is a commonly seen disease, and an accurate diagnosis of the type of CH is a very crucial step in treatment. Ther...

Physics-informed attention-based neural network for hyperbolic partial differential equations: application to the Buckley-Leverett problem.

Physics-informed neural networks (PINNs) have enabled significant improvements in modelling physical processes described by partial differential equat...

Deep Learning-Based Computed Tomography Perfusion Imaging to Evaluate the Effectiveness and Safety of Thrombolytic Therapy for Cerebral Infarct with Unknown Time of Onset.

This study was aimed to discuss the effectiveness and safety of deep learning-based computed tomography perfusion (CTP) imaging in the thrombolytic th...

Identifying Protein Features and Pathways Responsible for Toxicity Using Machine Learning and Tox21: Implications for Predictive Toxicology.

Humans are exposed to numerous compounds daily, some of which have adverse effects on health. Computational approaches for modeling toxicological data...

Machine learning model prediction of 6-month functional outcome in elderly patients with intracerebral hemorrhage.

Spontaneous intracerebral hemorrhage (ICH) has an increasing incidence and a worse outcome in elderly patients. The ability to predict the functional ...

Detecting and Extracting Brain Hemorrhages from CT Images Using Generative Convolutional Imaging Scheme.

PURPOSE: The need for computerized medical assistance for accurate detection of brain hemorrhage from Computer Tomography (CT) images is more mandator...

Replacement of animal testing by integrated approaches to testing and assessment (IATA): a call for in vivitrosi.

Alternative methods to animal use in toxicology are evolving with new advanced tools and multilevel approaches, to answer from one side to 3Rs require...

FractureNet: A 3D Convolutional Neural Network Based on the Architecture of m-Ary Tree for Fracture Type Identification.

To address the problem of automatic identification of fine-grained fracture types, in this paper, we propose a novel framework using 3D convolutional ...

Cardiac auscultation predicts mortality in elderly patients admitted for COVID-19.

INTRODUCTION: COVID-19 has had a great impact on the elderly population. All admitted patients underwent cardiac auscultation at the Emergency Departm...

POTTER-ICU: An artificial intelligence smartphone-accessible tool to predict the need for intensive care after emergency surgery.

BACKGROUND: Delays in admitting high-risk emergency surgery patients to the intensive care unit result in worse outcomes and increased health care cos...