Emergency Medicine

Labeling Noncontrast Head CT Reports for Common Findings Using Natural Language Processing.

BACKGROUND AND PURPOSE: Prioritizing reading of noncontrast head CT examinations through an automated triage system may improve time to care for patients with acute neuroradiologic findings. We present a natural language-processing approach for labeling findings in noncontrast head CT reports, which permits creation of a large, labeled dataset of head CT images for development of emergent-finding ...

Toward an artificial intelligence-assisted framework for reconstructing the digital twin of vertebra and predicting its fracture response.

This article presents an effort toward building an artificial intelligence (AI) assisted framework, coined ReconGAN, for creating a realistic digital twin of the human vertebra and predicting the risk of vertebral fracture (VF). ReconGAN consists of a deep convolutional generative adversarial network (DCGAN), image-processing steps, and finite element (FE) based shape optimization to reconstruct t...

Explainable detection of myocardial infarction using deep learning models with Grad-CAM technique on ECG signals.

Myocardial infarction (MI) accounts for a high number of deaths globally. In acute MI, accurate electrocardiography (ECG) is important for timely diag...

Computed Tomography Images under Artificial Intelligence Algorithms on the Treatment Evaluation of Intracerebral Hemorrhage with Minimally Invasive Aspiration.

The aim of this study was to investigate the therapeutic effect of minimally invasive aspiration on intracerebral hemorrhage (ICH) and the value of ar...

Predicting Neurological Outcome From Electroencephalogram Dynamics in Comatose Patients After Cardiac Arrest With Deep Learning.

OBJECTIVE: Most cardiac arrest patients who are successfully resuscitated are initially comatose due to hypoxic-ischemic brain injury. Quantitative el...

Vision Transformer for femur fracture classification.

INTRODUCTION: In recent years, the scientific community focused on developing Computer-Aided Diagnosis (CAD) tools that could improve clinicians' bone...

LightEyes: A Lightweight Fundus Segmentation Network for Mobile Edge Computing.

Fundus is the only structure that can be observed without trauma to the human body. By analyzing color fundus images, the diagnosis basis for various ...

Epidemiological survey, general blood biochemistry, and histological examination of slaughtered heavy horse breeds with hemorrhage in the adipose tissue in the crest of the neck.

Fifty-four slaughtered horses were classified into groups having adipose tissue in the crest of the neck with or without hemorrhage (AH and NH groups,...

Automatic hemorrhage segmentation on head CT scan for traumatic brain injury using 3D deep learning model.

The most common cause of long-term disability and death in young adults is a traumatic brain injury. The decision for surgical intervention for cranio...

Deep Learning and Microscopic Imaging in the Nursing Process of Neurosurgery Operation.

Neurosurgery is mainly for the treatment of head trauma, cerebrovascular disease, brain tumors, and spinal cord disorders. These operations are diffic...

Bayesian deep learning outperforms clinical trial estimators of intracerebral and intraventricular hemorrhage volume.

BACKGROUND AND PURPOSE: Intracerebral hemorrhage (ICH) and intraventricular hemorrhage (IVH) clinical trials rely on manual linear and semi-quantitati...

Deep Learning-Based Medical Information System in First Aid of Surgical Trauma.

The aim of this study was to explore the application of process reengineering integration in trauma first aid based on deep learning and medical infor...

Deep Transfer Learning for Automatic Prediction of Hemorrhagic Stroke on CT Images.

Intracerebral hemorrhage (ICH) is the most common type of hemorrhagic stroke which occurs due to ruptures of weakened blood vessel in brain tissue. It...

A hybrid resampling algorithms SMOTE and ENN based deep learning models for identification of Marburg virus inhibitors.

Marburg virus (MARV) is a sporadic outbreak of a zoonotic disease that causes lethal hemorrhagic fever in humans. We propose a deep learning model wi...

Prediction of femoral strength of elderly men based on quantitative computed tomography images using machine learning.

Hip fracture is the most common complication of osteoporosis, and its major contributor is compromised femoral strength. This study aimed to develop p...

A cost-aware framework for the development of AI models for healthcare applications.

Accurate artificial intelligence (AI) for disease diagnosis could lower healthcare workloads. However, when time or financial resources for gathering ...

Assessment of deep convolutional neural network models for mandibular fracture detection in panoramic radiographs.

The aim of this study was to develop automated models for the identification and detection of mandibular fractures in panoramic radiographs using conv...

Deep learning-based framework for segmentation of multiclass rib fractures in CT utilizing a multi-angle projection network.

PURPOSE: Clinical rib fracture diagnosis via computed tomography (CT) screening has attracted much attention in recent years. However, automated and a...

Endoscopic Enucleation of the Prostate Is Better than Robot-assisted Simple Prostatectomy.

In 2022, endoscopic enucleation of the prostate (EEP) is the treatment of choice for benign prostatic obstruction (BPO) for glands >80 ml and is a val...

Design and evaluation of an intelligent reduction robot system for the minimally invasive reduction in pelvic fractures.

INTRODUCTION: Pelvic fracture is a severe high-energy injury with the highest disability and mortality of all fractures. Traditional open surgery is a...