Emergency Medicine

Latest AI and machine learning research in emergency medicine for healthcare professionals.

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COVID-19 pneumonia on chest X-rays: Performance of a deep learning-based computer-aided detection system.

Chest X-rays (CXRs) can help triage for Coronavirus disease (COVID-19) patients in resource-constrai...

Musculoskeletal trauma and artificial intelligence: current trends and projections.

Musculoskeletal trauma accounts for a significant fraction of emergency department visits and patien...

Hemorrhage Detection Based on 3D CNN Deep Learning Framework and Feature Fusion for Evaluating Retinal Abnormality in Diabetic Patients.

Diabetic retinopathy (DR) is the main cause of blindness in diabetic patients. Early and accurate di...

Detecting pelvic fracture on 3D-CT using deep convolutional neural networks with multi-orientated slab images.

Pelvic fracture is one of the leading causes of death in the elderly, carrying a high risk of death ...

Improved liquid-liquid extraction by modified magnetic nanoparticles for the detection of eight drugs in human blood by HPLC-MS.

Magnetic nanoparticles modified with porous titanium dioxide were used as clean-up nanospheres for t...

Utilizing Whole Slide Images for the Primary Evaluation and Peer Review of a GLP-Compliant Rodent Toxicology Study.

The approach undertaken to deliver a Good Laboratory Practice (GLP) validation of whole slide images...

Clinical characteristics and oncological outcomes in negative multiparametric MRI patients undergoing robot-assisted radical prostatectomy.

BACKGROUND: Efforts are ongoing to try and find ways to reduce the number of unnecessary prostate bi...

Application of artificial intelligence for detection of chemico-biological interactions associated with oxidative stress and DNA damage.

In recent years, various AI-based methods have been developed in order to uncover chemico-biological...

Development and validation of a deep learning algorithm detecting 10 common abnormalities on chest radiographs.

We aimed to develop a deep learning algorithm detecting 10 common abnormalities (DLAD-10) on chest r...

Protein transfer learning improves identification of heat shock protein families.

Heat shock proteins (HSPs) play a pivotal role as molecular chaperones against unfavorable condition...

Comparison of machine-learning methodologies for accurate diagnosis of sepsis using microarray gene expression data.

We investigate the feasibility of molecular-level sample classification of sepsis using microarray g...

Differential diagnosis of benign and malignant vertebral fracture on CT using deep learning.

OBJECTIVES: To evaluate the performance of deep learning using ResNet50 in differentiation of benign...

Assessing the speed-accuracy trade-offs of popular convolutional neural networks for single-crop rib fracture classification.

Rib fractures are injuries commonly assessed in trauma wards. Deep learning has demonstrated state-o...

Diagnosis of Acute Poisoning using explainable artificial intelligence.

INTRODUCTION: Medical toxicology is the clinical specialty that treats the toxic effects of substanc...

Deep Learning for Hemorrhagic Lesion Detection and Segmentation on Brain CT Images.

Stroke is an acute cerebral vascular disease that is likely to cause long-term disabilities and deat...

COVID-Classifier: an automated machine learning model to assist in the diagnosis of COVID-19 infection in chest X-ray images.

Chest-X ray (CXR) radiography can be used as a first-line triage process for non-COVID-19 patients w...

Predicting venous thromboembolism in hospitalized trauma patients: a combination of the Caprini score and data-driven machine learning model.

BACKGROUND: Venous thromboembolism (VTE) is a common complication of hospitalized trauma patients an...

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