Sexual Assault

A multicenter mixed-effects model for inference and prediction of 72-h return visits to the emergency department for adult patients with trauma-related diagnoses.

OBJECTIVE: Emergency department (ED) return visits within 72 h may be a sign of poor quality of care and entail unnecessary use of healthcare resources. In this study, we compare the performance of two leading statistical and machine learning classification algorithms, and we use the best performing approach to identify novel risk factors of ED return visits.

A Single-Center Evaluation of Extended Infusion Piperacillin/Tazobactam for Empiric Treatment in the Intensive Care Unit.

Piperacillin/tazobactam (PTZ) extended infusion (EI) is often used empirically in the intensive care unit (ICU). Gram-negative (GN) organisms with PTZ minimum inhibitory concentrations (MICs) >16/4 µg/mL are considered intermediate or resistant. The objective of this study was to evaluate MICs of GN isolates from the ICU to determine whether the hospital protocol for PTZ 3.375 g EI over 4 hours ...

Deep learning-based classification of posttraumatic stress disorder and depression following trauma utilizing visual and auditory markers of arousal and mood.

BACKGROUND: Visual and auditory signs of patient functioning have long been used for clinical diagnosis, treatment selection, and prognosis. Direct me...

Predicting Crash Injury Severity with Machine Learning Algorithm Synergized with Clustering Technique: A Promising Protocol.

Predicting crash injury severity is a crucial constituent of reducing the consequences of traffic crashes. This study developed machine learning (ML) ...

Acceptance and Commitment Therapy Delivered via a Mobile Phone Messaging Robot to Decrease Postoperative Opioid Use in Patients With Orthopedic Trauma: Randomized Controlled Trial.

BACKGROUND: Acceptance and commitment therapy (ACT) is a pragmatic approach to help individuals decrease avoidable pain.

Major depressive disorder diagnosis based on effective connectivity in EEG signals: a convolutional neural network and long short-term memory approach.

Deep learning techniques have recently made considerable advances in the field of artificial intelligence. These methodologies can assist psychologist...

Magnetic Resonance Guided Navigation of Untethered Microgrippers.

Microsurgical tools offer a path to less invasive clinical procedures with improved access, reduced trauma, and better recovery outcomes. There are a ...

The first use of artificial intelligence (AI) in the ER: triage not diagnosis.

Predictions related to the impact of AI on radiology as a profession run the gamut from AI putting radiologists out of business to having no effect at...

Using trauma registry data to predict prolonged mechanical ventilation in patients with traumatic brain injury: Machine learning approach.

OBJECTIVES: We aimed to build a machine learning predictive model to predict the risk of prolonged mechanical ventilation (PMV) for patients with Trau...

Utilization of machine learning to test the impact of cognitive processing and emotion recognition on the development of PTSD following trauma exposure.

BACKGROUND: Though lifetime exposure to traumatic events is significant, only a minority of individuals develops symptoms of posttraumatic stress diso...

Prediction of in-hospital mortality in patients with post traumatic brain injury using National Trauma Registry and Machine Learning Approach.

BACKGROUND: The use of machine learning techniques to predict diseases outcomes has grown significantly in the last decade. Several studies prove that...

Fully Automated Segmentation of Globes for Volume Quantification in CT Images of Orbits using Deep Learning.

BACKGROUND AND PURPOSE: Fast and accurate quantification of globe volumes in the event of an ocular trauma can provide clinicians with valuable diagno...

A Comparison between Several Response Surface Methodology Designs and a Neural Network Model to Optimise the Oxidation Conditions of a Lignocellulosic Blend.

In this paper, response surface methodology (RSM) designs and an artificial neural network (ANN) are used to obtain the optimal conditions for the oxy...

Rape narratives analysis through natural language processing: Survivor self-label, narrative time span, faith, and rape terminology.

OBJECTIVE: Rape-survivor identity is a sign of recovery and positive therapeutic progress among rape victims. This study is one of the few to focus on...

Association Rule Learning Is an Easy and Efficient Method for Identifying Profiles of Traumas and Stressors that Predict Psychopathology in Disaster Survivors: The Example of Sri Lanka.

Research indicates that psychopathology in disaster survivors is a function of both experienced trauma and stressful life events. However, such studie...

Exploring the Role of Artificial Intelligence in an Emergency and Trauma Radiology Department.

Emergency and trauma radiologists, emergency department's physicians and nurses, researchers, departmental leaders, and health policymakers have attem...

Multi-Scale deep learning framework for cochlea localization, segmentation and analysis on clinical ultra-high-resolution CT images.

BACKGROUND AND OBJECTIVE: Performing patient-specific, pre-operative cochlea CT-based measurements could be helpful to positively affect the outcome o...

Prediction of Early TBI Mortality Using a Machine Learning Approach in a LMIC Population.

In a time when the incidence of severe traumatic brain injury (TBI) is increasing in low- to middle-income countries (LMICs), it is important to unde...

Early Recognition of Burn- and Trauma-Related Acute Kidney Injury: A Pilot Comparison of Machine Learning Techniques.

Severely burned and non-burned trauma patients are at risk for acute kidney injury (AKI). The study objective was to assess the theoretical performanc...

Machine learning for the detection of early immunological markers as predictors of multi-organ dysfunction.

The immune response to major trauma has been analysed mainly within post-hospital admission settings where the inflammatory response is already underw...