Emergency Medicine

Automatic detection of midfacial fractures in facial bone CT images using deep learning-based object detection models.

BACKGROUND: Midfacial fractures are among the most frequent facial fractures. Surgery is recommended within 2 weeks of injury, but this time frame is often extended because the fracture is missed on diagnostic imaging in the busy emergency medicine setting. Using deep learning technology, which has progressed markedly in various fields, we attempted to develop a system for the automatic detection ...

Interpretable machine learning predicts postpartum hemorrhage at time of admission.

Predicting hematoma expansion using machine learning: An exploratory analysis of the ATACH 2 trial.

INTRODUCTION: Hematoma expansion (HE) in patients with intracerebral hemorrhage (ICH) is a key predictor of poor prognosis and potentially amenable to...

Predicting early mortality and severe intraventricular hemorrhage in very-low birth weight preterm infants: a nationwide, multicenter study using machine learning.

Our aim was to develop a machine learning-based predictor for early mortality and severe intraventricular hemorrhage (IVH) in very-low birth weight (V...

Can Artificial Intelligence Be Utilized to Predict Real-Time Adverse Outcomes in Individuals Arriving at the Emergency Department With Hyperglycemic Crises?: Implications for APRN Practice.

This column on translating research into practice is crafted to offer advanced practice registered nurses an analysis of current research topics that ...

Predicting blood transfusion following traumatic injury using machine learning models: A systematic review and narrative synthesis.

BACKGROUND: Hemorrhage is a leading cause of preventable death in trauma. Accurately predicting a patient's blood transfusion requirement is essential...

Machine learning as a hopeful indicator for prediction of complications and mortality in burn patients.

Patient's airway monitoring during cardiopulmonary resuscitation using deep networks.

Cardiopulmonary resuscitation (CPR) is a crucial life-saving technique commonly administered to individuals experiencing cardiac arrest. Among the imp...

An efficient deep neural network for automatic classification of acute intracranial hemorrhages in brain CT scans.

BACKGROUND: Recent advancements in deep learning models have demonstrated their potential in the field of medical imaging, achieving remarkable perfor...

Predicting osteoporotic fractures post-vertebroplasty: a machine learning approach with a web-based calculator.

PURPOSE: The aim of this study was to develop and validate a machine learning (ML) model for predicting the risk of new osteoporotic vertebral compres...

Safety and Efficacy of Acute Central Venous Catheters for Hemodialysis with Sodium Bicarbonate versus an Antibiotic Catheter Locking Solution.

This study was conducted to determine the safety and efficacy of acute central venous catheters (CVC) using a sodium bicarbonate catheter locking solu...

AMPred-CNN: Ames mutagenicity prediction model based on convolutional neural networks.

Mutagenicity assessment plays a pivotal role in the safety evaluation of chemicals, pharmaceuticals, and environmental compounds. In recent years, the...

Using machine learning to increase access to and engagement with trauma-focused interventions for posttraumatic stress disorder.

BACKGROUND: Post-traumatic stress disorder (PTSD) poses a global public health challenge. Evidence-based psychotherapies (EBPs) for PTSD reduce sympto...

Evaluating Deep Learning Techniques for Detecting Aneurysmal Subarachnoid Hemorrhage: A Comparative Analysis of Convolutional Neural Network and Transfer Learning Models.

OBJECTIVE: Machine learning and deep learning techniques offer a promising multidisciplinary solution for subarachnoid hemorrhage (SAH) detection. The...

The application of deep learning in abdominal trauma diagnosis by CT imaging.

BACKGROUND: Abdominal computed tomography (CT) scan is a crucial imaging modality for creating cross-sectional images of the abdominal area, particula...

Can Machine Learning Personalize Cardiovascular Therapy in Sepsis?

Large randomized trials in sepsis have generally failed to find effective novel treatments. This is increasingly attributed to patient heterogeneity, ...

Intensive longitudinal assessment following index trauma to predict development of PTSD using machine learning.

There are significant challenges to identifying which individuals require intervention following exposure to trauma, and a need for strategies to iden...

Evaluating the Quality of Postpartum Hemorrhage Nursing Care Plans Generated by Artificial Intelligence Models.

BACKGROUND: With the rapidly advancing technological landscape of health care, evaluating the potential use of artificial intelligence (AI) models to ...

Use of an Artificial Intelligence Device for Evaluating Blood Loss in Complex Major Orthopaedic Surgery Procedures.

BACKGROUND: An artificial intelligence algorithm that analyzes the pulse oximeter waveform in the fingertip can be used to determine the compensatory ...

Enhancing pneumonia prognosis in the emergency department: a novel machine learning approach using complete blood count and differential leukocyte count combined with CURB-65 score.

BACKGROUND: Pneumonia poses a major global health challenge, necessitating accurate severity assessment tools. However, conventional scoring systems s...