Emergency Medicine

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

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Automatic detection of 39 fundus diseases and conditions in retinal photographs using deep neural networks.

Retinal fundus diseases can lead to irreversible visual impairment without timely diagnoses and appr...

Deep learning and lung ultrasound for Covid-19 pneumonia detection and severity classification.

The Covid-19 European outbreak in February 2020 has challenged the world's health systems, eliciting...

Development and Assessment of an Interpretable Machine Learning Triage Tool for Estimating Mortality After Emergency Admissions.

IMPORTANCE: Triage in the emergency department (ED) is a complex clinical judgment based on the taci...

Documentation of Shared Decisionmaking in the Emergency Department.

STUDY OBJECTIVE: While patient-centered communication and shared decisionmaking are increasingly rec...

Beyond motor recovery after stroke: The role of hand robotic rehabilitation plus virtual reality in improving cognitive function.

Robot-assisted hand training adopting end-effector devices results in an additional reduction of mot...

Intelligent Disease Prediagnosis Only Based on Symptoms.

People often concern the relationships between symptoms and diseases when seeking medical advices. I...

Predicting pain among female survivors of recent interpersonal violence: A proof-of-concept machine-learning approach.

Interpersonal violence (IPV) is highly prevalent in the United States and is a major public health p...

Ensuring Adequate Development and Appropriate Use of Artificial Intelligence in Pediatric Medical Imaging.

Of over 100 FDA-cleared artificial intelligence (AI) tools for triage, detection, or diagnosis in me...

What's in a trauma? Using machine learning to unpack what makes an event traumatic.

What differentiates a trauma from an event that is merely upsetting? Wildly different definitions of...

Bone collision detection method for robot assisted fracture reduction based on force curve slope.

BACKGROUND AND OBJECTIVE: The application of robot technology in fracture reduction ensures the mini...

Platform for Healthcare Promotion and Cardiovascular Disease Prevention.

This article presents the hardware-software design and implementation of an open, integrated, and sc...

Deep Learning in the Detection of Rare Fractures - Development of a "Deep Learning Convolutional Network" Model for Detecting Acetabular Fractures.

BACKGROUND: Fracture detection by artificial intelligence and especially Deep Convolutional Neural N...

Emerging Technologies for In Vitro Inhalation Toxicology.

Respiratory toxicology remains a major research area in the 21st century since current scenario of a...

A systematic review of machine learning and automation in burn wound evaluation: A promising but developing frontier.

BACKGROUND: Visual evaluation is the most common method of evaluating burn wounds. Its subjective na...

Combination Therapy of Chloramphenicol and Daptomycin for the Treatment of Infective Endocarditis Secondary to Multidrug Resistant .

A 38-years-old female with an aortic valve replacement presented to an outside hospital (OSH) with f...

Machine learning for selecting patients with Crohn's disease for abdominopelvic computed tomography in the emergency department.

BACKGROUND: Patients with Crohn's disease (CD) frequently undergo abdominopelvic computed tomography...

CRP (C-Reactive Protein) in Outcome Prediction After Subarachnoid Hemorrhage and the Role of Machine Learning.

BACKGROUND AND PURPOSE: Outcome prediction after aneurysmal subarachnoid hemorrhage (aSAH) is challe...

Automated Vertebral Segmentation and Measurement of Vertebral Compression Ratio Based on Deep Learning in X-Ray Images.

Vertebral compression fracture is a deformity of vertebral bodies found on lateral spine images. To ...

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