Emergency Medicine

Applications of deep learning in trauma radiology: A narrative review.

Diagnostic imaging is essential in modern trauma care for initial evaluation and identifying injurie...

Behavioral toxicological tracking analysis of Drosophila larvae exposed to polystyrene microplastics based on machine learning.

Microplastics, as a pivotal concern within plastic pollution, have sparked widespread apprehension d...

Application of deep learning and radiomics in the prediction of hematoma expansion in intracerebral hemorrhage: a fully automated hybrid approach.

PURPOSE: Spontaneous intracerebral hemorrhage (ICH) is the most severe form of stroke. The timely as...

YOLOX-SwinT algorithm improves the accuracy of AO/OTA classification of intertrochanteric fractures by orthopedic trauma surgeons.

PURPOSE: Intertrochanteric fracture (ITF) classification is crucial for surgical decision-making. Ho...

BiliQML: a supervised machine-learning model to quantify biliary forms from digitized whole slide liver histopathological images.

The progress of research focused on cholangiocytes and the biliary tree during development and follo...

AI triage in general practice will remove the crucial human touch.

An explainable machine learning framework for predicting the risk of buprenorphine treatment discontinuation for opioid use disorder among commercially insured individuals.

OBJECTIVES: Buprenorphine is an effective evidence-based medication for opioid use disorder (OUD). Y...

An ensemble model for predicting dispositions of emergency department patients.

OBJECTIVE: The healthcare challenge driven by an aging population and rising demand is one of the mo...

Prediction of high-risk emergency department revisits from a machine-learning algorithm: a proof-of-concept study.

BACKGROUND: High-risk emergency department (ED) revisit is considered an important quality indicator...

Using an artificial intelligence software improves emergency medicine physician intracranial haemorrhage detection to radiologist levels.

BACKGROUND: Tools to increase the turnaround speed and accuracy of imaging reports could positively ...

Artificial intelligence diagnostic accuracy in fracture detection from plain radiographs and comparing it with clinicians: a systematic review and meta-analysis.

PURPOSE: Fracture detection is one of the most commonly used and studied aspects of artificial intel...

Potential of artificial intelligence in public health disaster and emergency management.

Deep learning model for pleural effusion detection via active learning and pseudo-labeling: a multisite study.

BACKGROUND: The study aimed to develop and validate a deep learning-based Computer Aided Triage (CAD...

Application of machine learning and multivariate approaches for assessing microplastic pollution and its associated risks in the urban outdoor environment of Bangladesh.

Microplastics (MPs) are an emerging global concern due to severe toxicological risks for ecosystems ...

Postoperative leukocyte counts as a surrogate for surgical stress response in matched robot- and video-assisted thoracoscopic surgery cohorts of patients: A preliminary report.

The objective is to preliminary evaluated postoperative leukocyte counts as a surrogate for the surg...

How artificial intelligence could transform emergency care.

Artificial intelligence (AI) in healthcare is the ability of a computer to perform tasks typically a...

Chemometrics-driven prediction and prioritization of diverse pesticides on chickens for addressing hazardous effects on public health.

The extensive use of various pesticides in the agriculture field badly affects both chickens and hum...

Development and Internal Validation of a Multivariable Prediction Model for Mortality After Hip Fracture with Machine Learning Techniques.

In order to estimate the likelihood of 1, 3, 6 and 12 month mortality in patients with hip fractures...

An Automated Multi-scale Feature Fusion Network for Spine Fracture Segmentation Using Computed Tomography Images.

Spine fractures represent a critical health concern with far-reaching implications for patient care ...

Harnessing machine learning to predict cytochrome P450 inhibition through molecular properties.

Cytochrome P450 enzymes are a superfamily of enzymes responsible for the metabolism of a variety of ...

Effect of on neurological function in acute aneurysmal subarachnoid hemorrhage patients with high inflammation: A preliminary randomized, double-blind, placebo-controlled clinical trial.

BACKGROUND AND AIM: (AM) is a traditional Chinese herb. Our previous study revealed that AM can enh...