Emergency Medicine

DL4Burn: Burn Surgical Candidacy Prediction using Multimodal Deep Learning.

Burn wounds are most commonly evaluated through visual inspection to determine surgical candidacy, taking into account burn depth and individualized patient factors. This process, though cost effective, is subjective and varies by provider experience. Deep learning models can assist in burn wound surgical candidacy with predictions based on the wound and patient characteristics. To this end, we pr...

Bias Assessment and Correction in Machine Learning Algorithms: A Use-Case in a Natural Language Processing Algorithm to Identify Hospitalized Patients with Unhealthy Alcohol Use.

Unhealthy alcohol use represents a major economic burden and cause of morbidity and mortality in the United States. Implementation of interventions for unhealthy alcohol use depends on the availability and accuracy of screening tools. Our group previously applied methods in natural language processing and machine learning to build a classifier for unhealthy alcohol use. In this study, we sought to...

Prediction of Resuscitation for Pediatric Sepsis from Data Available at Triage.

Pediatric sepsis imposes a significant burden of morbidity and mortality among children. While the speedy application of existing supportive care meas...

Real-time data analysis in health monitoring systems: A comprehensive systematic literature review.

Health monitoring systems (HMSs) capture physiological measurements through biosensors (sensing), obtain significant properties and measures from the ...

Accelerating susceptibility-weighted imaging with deep learning by complex-valued convolutional neural network (ComplexNet): validation in clinical brain imaging.

OBJECTIVES: Susceptibility-weighted imaging (SWI) is crucial for the characterization of intracranial hemorrhage and mineralization, but has the drawb...

Three-dimensional deep learning to automatically generate cranial implant geometry.

We present a 3D deep learning framework that can generate a complete cranial model using a defective one. The Boolean subtraction between these two mo...

Machine learning-based prediction of critical illness in children visiting the emergency department.

OBJECTIVES: Triage is an essential emergency department (ED) process designed to provide timely management depending on acuity and severity; however, ...

Operating Room Planning for Emergency Surgery: Optimization in Multiobjective Modeling and Management from the Latest Developments in Computational Intelligence Techniques.

This study presents an optimization approach for scheduling the operation room for emergency surgeries, considering the priority of surgeries. This op...

Automatic detection and classification of peri-prosthetic femur fracture.

PURPOSE: Object classification and localization is a key task of computer-aided diagnosis (CAD) tool. Although there have been numerous generic deep l...

Selecting Machine Learning Models to Support the Design of Al/CuO Nanothermites.

Novel properties associated with nanothermites have attracted great interest for several applications, including lead-free primers and igniters. Howev...

Robot-assisted Total Mesorectal Excision and Lateral Pelvic Lymph Node Dissection for Locally Advanced Middle-low Rectal Cancer.

Since their approval for clinical use, da Vinci surgical robots have shown great advantages in gastrointestinal surgical operations, especially in com...

Application of Deep Learning to Ischemic and Hemorrhagic Stroke Computed Tomography and Magnetic Resonance Imaging.

Deep Learning (DL) algorithm holds great potential in the field of stroke imaging. It has been applied not only to the "downstream" side such as lesio...

Knowledge, attitude, and practice of artificial intelligence in emergency and trauma surgery, the ARIES project: an international web-based survey.

AIM: We aimed to evaluate the knowledge, attitude, and practices in the application of AI in the emergency setting among international acute care and ...

Safety and efficacy of a novel robotic transcranial doppler system in subarachnoid hemorrhage.

Delayed cerebral ischemia (DCI) secondary to vasospasm is a determinate of outcomes following non-traumatic subarachnoid hemorrhage (SAH). SAH patient...

Pediatric Otoscopy Video Screening With Shift Contrastive Anomaly Detection.

Ear related concerns and symptoms represent the leading indication for seeking pediatric healthcare attention. Despite the high incidence of such enco...

Trajectory optimisation with musculoskeletal integration features for fracture reduction orthopaedic robot.

BACKGROUND: Human body is an integrated system of bones and muscles. To date, there are insufficient studies on the effect of muscles on the trajector...

Actuation-Augmented Biohybrid Robot by Hyaluronic Acid-Modified Au Nanoparticles in Muscle Bundles to Evaluate Drug Effects.

Biohybrid robots, which comprise soft materials with biological components, have the potential to sense, respond, and adapt to changing environmental ...

Machine learning outperforms clinical experts in classification of hip fractures.

Hip fractures are a major cause of morbidity and mortality in the elderly, and incur high health and social care costs. Given projected population age...

A joint convolutional-recurrent neural network with an attention mechanism for detecting intracranial hemorrhage on noncontrast head CT.

To investigate the performance of a joint convolutional neural networks-recurrent neural networks (CNN-RNN) using an attention mechanism in identifyin...

Fracture Detection in Wrist X-ray Images Using Deep Learning-Based Object Detection Models.

Hospitals, especially their emergency services, receive a high number of wrist fracture cases. For correct diagnosis and proper treatment of these, im...