Head Trauma

Identifying probable post-traumatic stress disorder: applying supervised machine learning to data from a UK military cohort.

BACKGROUND: Early identification of probable post-traumatic stress disorder (PTSD) can lead to early intervention and treatment.

Non-directed bronchial lavage is a safe method for sampling the respiratory tract in critically ill patient.

Ventilated patients are at risk of acquiring ventilator-associated pneumonia. Various techniques are available for diagnosing ventilator-associated pneumonia including bronchoalveolar lavage, protected specimen brush and non-directed bronchoalveolar lavage. There is a paucity of evidence regarding the safety profile of these techniques, particularly non-directed bronchoalveolar lavage. This servic...

Mortality prediction in patients with isolated moderate and severe traumatic brain injury using machine learning models.

BACKGROUND: The purpose of this study was to build a model of machine learning (ML) for the prediction of mortality in patients with isolated moderate...

A Randomized Control Trial Of Anti-Inflammatory Regional Hypothermia On Urinary Continence During Robot-Assisted Radical Prostatectomy.

The present study seeks to present a single-blind, randomized control trial of a hypothermic anti-inflammatory device, the endorectal cooling balloon ...

Using an artificial neural network to predict traumatic brain injury.

In BriefPediatric traumatic brain injury (TBI) is common, but not all injuries require hospitalization. A computational tool for ruling-in patients wh...

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 ...

Social-cue perception and mentalizing ability following traumatic brain injury: A human-robot interaction study.

PRIMARY OBJECTIVE: Research studies and clinical observations of individuals with traumatic brain injury (TBI) indicate marked deficits in mentalizing...

Novel screening criteria for post-traumatic venous thromboembolism by using D-dimer.

AIM: Because severe trauma patients frequently manifest coagulopathy, it is extremely important to detect venous thromboembolism (VTE) in the acute ph...

Mining User-Generated Content in an Online Smoking Cessation Community to Identify Smoking Status: A Machine Learning Approach.

Online smoking cessation communities help hundreds of thousands of smokers quit smoking and stay abstinent each year. Content shared by users of such ...

Minimally invasive, robot-assisted procedure for kidney transplantation among morbidly obese: Positive outcomes at 5 years post-transplant.

The pre-transplant weight loss required of end-stage renal disease patients is often unachievable. Though robot-assisted procedures among extremely ob...

Comparison of radiomics machine-learning classifiers and feature selection for differentiation of sacral chordoma and sacral giant cell tumour based on 3D computed tomography features.

OBJECTIVE: We aimed to identify optimal machine-learning methods for preoperative differentiation of sacral chordoma (SC) and sacral giant cell tumour...

Optimal cerebral perfusion pressure via transcranial Doppler in TBI: application of robotic technology.

Individualized cerebral perfusion pressure (CPP) targets may be derived via assessing the minimum of the parabolic relationship between an index of ce...

Experimental infection of Friesian bulls with Theileria orientalis (Ikeda) and effects on the haematocrit, live weight, rectal temperature and activity.

Since 2012, New Zealand has suffered from an epidemic of infectious bovine anaemia associated with T. orientalis (Ikeda), an obligate intracellular pr...

Robotic technology provides objective and quantifiable metrics of neurocognitive functioning in survivors of critical illness:A feasibility study.

PURPOSE: To assess the feasibility of using an integrated multimodal data collection strategy to characterize the post-intensive care syndrome (PICS).

Segmenting the Brain Surface From CT Images With Artifacts Using Locally Oriented Appearance and Dictionary Learning.

The accurate segmentation of the brain surface in post-surgical computed tomography (CT) images is critical for image-guided neurosurgical procedures ...

Predictors of atrial fibrillation early recurrence following cryoballoon ablation of pulmonary veins using statistical assessment and machine learning algorithms.

Inflammation, oxidative stress, myocardial injury biomarkers and clinical parameters (longer AF duration, left atrial enlargement, the metabolic syndr...

Mining patterns of comorbidity evolution in patients with multiple chronic conditions using unsupervised multi-level temporal Bayesian network.

Over the past few decades, the rise of multiple chronic conditions has become a major concern for clinicians. However, it is still not known precisely...

The effects of error-augmentation versus error-reduction paradigms in robotic therapy to enhance upper extremity performance and recovery post-stroke: a systematic review.

Despite upper extremity function playing a crucial role in maintaining one's independence in activities of daily living, upper extremity impairments r...

Forewarning of hypotensive events using a Bayesian artificial neural network in neurocritical care.

Traumatically brain injured (TBI) patients are at risk from secondary insults. Arterial hypotension, critically low blood pressure, is one of the most...

Open Globe Injury Patient Identification in Warfare Clinical Notes.

The aim of this study is to utilize the Defense and Veterans Eye Injury and Vision Registry clinical data derived from DoD and VA medical systems whic...