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Identifying bladder rupture following traumatic pelvic fracture: A machine learning approach.

INTRODUCTION: Bladder rupture following blunt pelvic trauma is rare though can have significant sequelae. We sought to determine whether machine learning could help predict the presence of bladder injury using certain factors at the time of presentation of blunt pelvic trauma.

The use of machine learning techniques in trauma-related disorders: a systematic review.

Establishing the diagnosis of trauma-related disorders such as Acute Stress Disorder (ASD) and Posttraumatic Stress Disorder (PTSD) have always been a challenge in clinical practice and in academic research, due to clinical and biological heterogeneity. Machine learning (ML) techniques can be applied to improve classification of disorders, to predict outcomes or to determine person-specific treatm...

Twin Robotic X-Ray System for 3D Cone-Beam CT of the Wrist: An Evaluation of Image Quality and Radiation Dose.

The purpose of this study was to assess image quality and radiation dose of a novel twin robotic x-ray system's 3D cone-beam CT (CBCT) function for t...

Robot-assisted flexible needle insertion using universal distributional deep reinforcement learning.

PURPOSE: Flexible needle insertion is an important minimally invasive surgery approach for biopsy and radio-frequency ablation. This approach can mini...

Machine-learned analysis of side-differences in odor identification performance.

A right-left dichotomy of olfactory processes has been recognized on several levels of the perception or processing of olfactory input. On a clinical ...

Drainage Collection After Endoscopic-Assisted Transaxillary Dual-Plane Augmentation Mammaplasty Using Cold or Electrosurgical Separation of Interpectoral Space.

BACKGROUND: Endoscopic transaxillary augmentation mammaplasty breast augmentation offers several advantages over other augmentation methods. Nonethele...

Validation of an alcohol misuse classifier in hospitalized patients.

BACKGROUND: Current modes of identifying alcohol misuse in hospitalized patients rely on self-report questionnaires and diagnostic codes that have lim...

A Concentric Tube Robot System for Rigid Bronchoscopy: A Feasibility Study on Central Airway Obstruction Removal.

New robotic systems have recently emerged to assist with peripheral lung access, but a robotic system for rigid bronchoscopy has yet to be developed. ...

Modelling disease risk for amyloid A (AA) amyloidosis in non-human primates using machine learning.

Amyloid A (AA) amyloidosis is found in humans and non-human primates, but quantifying disease risk prior to clinical symptoms is challenging. We appl...

Dynamic multi-outcome prediction after injury: Applying adaptive machine learning for precision medicine in trauma.

OBJECTIVE: Machine learning techniques have demonstrated superior discrimination compared to conventional statistical approaches in predicting trauma ...

Machine Learning for Prediction of Posttraumatic Stress and Resilience Following Trauma: An Overview of Basic Concepts and Recent Advances.

Posttraumatic stress responses are characterized by a heterogeneity in clinical appearance and etiology. This heterogeneity impacts the field's abilit...

Prediction of cervical spine injury in young pediatric patients: an optimal trees artificial intelligence approach.

BACKGROUND: Cervical spine injuries (CSI) are a major concern in young pediatric trauma patients. The consequences of missed injuries and difficulties...

The trauma severity model: An ensemble machine learning approach to risk prediction.

Statistical theory indicates that a flexible model can attain a lower generalization error than an inflexible model, provided that the setting is appr...

Identification of a closed cutaneous injury after mechanical trauma caused by collision.

PURPOSE: Robotics has evolved rapidly in terms of mechanical design and control in the past few years. Collaborative robots that have direct contact w...

Comparison of artificial neural network and logistic regression models for prediction of outcomes in trauma patients: A systematic review and meta-analysis.

BACKGROUND: Currently, two models of artificial neural network (ANN) and logistic regression (LR) are known as models that extensively used in medical...

Defining Massive Transfusion in Civilian Pediatric Trauma With Traumatic Brain Injury.

The purpose of this study was to identify an optimal definition of massive transfusion in civilian pediatric trauma with severe traumatic brain injury...

Robot assisted minimally invasive esophagectomy (RAMIE) for esophageal cancer.

Worldwide, the standard treatment for locally advanced esophageal cancer with curative intent is perioperative chemotherapy or preoperative chemoradio...

The Healthy Children, Strong Families 2 (HCSF2) Randomized Controlled Trial Improved Healthy Behaviors in American Indian Families with Young Children.

BACKGROUND: American Indian (AI) families experience a disproportionate risk of obesity due to a number of complex reasons, including poverty, histori...

Ensemble machine learning prediction of posttraumatic stress disorder screening status after emergency room hospitalization.

Posttraumatic stress disorder (PTSD) develops in a substantial minority of emergency room admits. Inexpensive and accurate person-level assessment of ...

A data-driven artificial intelligence model for remote triage in the prehospital environment.

In a mass casualty incident, the factors that determine the survival rate of injured patients are diverse, but one of the key factors is the time for ...