Emergency Medicine

Risk assessment for intra-abdominal injury following blunt trauma in children: Derivation and validation of a machine learning model.

BACKGROUND: Computed tomography is the criterion standard for diagnosing intra-abdominal injury (IAI...

Assessment of a Deep Learning Algorithm for the Detection of Rib Fractures on Whole-Body Trauma Computed Tomography.

OBJECTIVE: To assess the diagnostic performance of a deep learning-based algorithm for automated det...

Classification of Intracranial Hemorrhage Subtypes Using Deep Learning on CT Scans.

Intracranial hemorrhage is a pathological condition that requires fast diagnosis and decision making...

Mobile Robotic Telepresence Between Hospital and School: Lessons Learned.

If a pupil falls seriously ill, it is not only a shock for the pupil himself or herself, but also fo...

Investigating the Barriers to Physician Adoption of an Artificial Intelligence- Based Decision Support System in Emergency Care: An Interpretative Qualitative Study.

The development of artificial intelligence (AI) systems to support diagnostic decision-making is rap...

Limited evidence of benefits of patient operated intelligent primary care triage tools: findings of a literature review.

INTRODUCTION: There is consistent evidence that the workload in general practices is substantially i...

Machine Learning Prediction of Postoperative Emergency Department Hospital Readmission.

BACKGROUND: Although prediction of hospital readmissions has been studied in medical patients, it ha...

Natural language processing of prehospital emergency medical services trauma records allows for automated characterization of treatment appropriateness.

BACKGROUND: Incomplete prehospital trauma care is a significant contributor to preventable deaths. C...

A new risk stratification score for patients with suspected cardiac chest pain in emergency departments, based on machine learning.

[Advances in the research of artificial intelligence technology assisting the diagnosis of burn depth].

The early accurate diagnosis of burn depth is of great significance in determining the corresponding...

Acceptability and Perceived Utility of Telemedical Consultation during Cardiac Arrest Resuscitation. A Multicenter Survey.

Many clinicians who participate in or lead in-hospital cardiac arrest (IHCA) resuscitations lack co...

[Detection of inferior myocardial infarction based on densely connected convolutional neural network].

Inferior myocardial infarction is an acute ischemic heart disease with high mortality, which is easy...

Determination of Electrocution Using Fourier Transform Infrared Microspectroscopy and Machine Learning Algorithm.

Objective To analyze the differences among electrical damage, burns and abrasions in pig skin using ...

Using a Dual-Input Convolutional Neural Network for Automated Detection of Pediatric Supracondylar Fracture on Conventional Radiography.

OBJECTIVES: This study aimed to develop a dual-input convolutional neural network (CNN)-based deep-l...

Performance of a Deep Learning Algorithm for Automated Segmentation and Quantification of Traumatic Pelvic Hematomas on CT.

The volume of pelvic hematoma at CT has been shown to be the strongest independent predictor of majo...

Computer-Aided Detection of Incidental Lumbar Spine Fractures from Routine Dual-Energy X-Ray Absorptiometry (DEXA) Studies Using a Support Vector Machine (SVM) Classifier.

To assess whether application of a support vector machine learning algorithm to ancillary data obtai...

Evaluating the Effect of Dexmedetomidine on Hemodynamic Status of Patients with Septic Shock Admitted to Intensive Care Unit: A Single-Blind Randomized Controlled Trial.

Septic shock, known as the most severe complication of sepsis, is a serious medical condition that c...

Postimplementation Evaluation of a Machine Learning-Based Deterioration Risk Alert to Enhance Sepsis Outcome Improvements.

Machine learning-based early warning systems (EWSs) can detect clinical deterioration more accuratel...

Diagnosis of Osteoporosis using modified U-net architecture with attention unit in DEXA and X-ray images.

BACKGROUND: Osteoporosis, a silent killing disease of fracture risk, is normally determined based on...

Use of artificial intelligence in imaging in rheumatology - current status and future perspectives.

After decades of basic research with many setbacks, artificial intelligence (AI) has recently obtain...

A Machine Learning-Based Model to Predict Acute Traumatic Coagulopathy in Trauma Patients Upon Emergency Hospitalization.

Acute traumatic coagulopathy (ATC) is an extremely common but silent murderer; this condition presen...