Sexual Assault

On Scene Injury Severity Prediction (OSISP) model for trauma developed using the Swedish Trauma Registry.

BACKGROUND: Providing optimal care for trauma, the leading cause of death for young adults, remains a challenge e.g., due to field triage limitations in assessing a patient's condition and deciding on transport destination. Data-driven On Scene Injury Severity Prediction (OSISP) models for motor vehicle crashes have shown potential for providing real-time decision support. The objective of this st...

Differentiating spinal pathologies by deep learning approach.

BACKGROUND CONTEXT: Spinal pathologies are diverse in nature and, excluding trauma and degenerative diseases, includes infectious, neoplastic (either extradural or intradural), and inflammatory conditions. The preoperative diagnosis is made with clinical judgment incorporating lab findings and radiological studies. When the diagnosis is uncertain, a biopsy is almost always mandatory since the trea...

Current knowledge and availability of machine learning across the spectrum of trauma science.

PURPOSE OF REVIEW: Recent technological advances have accelerated the use of Machine Learning in trauma science. This review provides an overview on t...

TraumaICD Bidirectional Encoder Representation From Transformers: A Natural Language Processing Algorithm to Extract Injury International Classification of Diseases, 10th Edition Diagnosis Code From Free Text.

OBJECTIVE: To develop and validate TraumaICDBERT, a natural language processing algorithm to predict injury International Classification of Diseases, ...

Enhancing the clinical relevance of haemorrhage prediction models in trauma.

An Artificial Intelligence Model for Predicting Trauma Mortality Among Emergency Department Patients in South Korea: Retrospective Cohort Study.

BACKGROUND: Within the trauma system, the emergency department (ED) is the hospital's first contact and is vital for allocating medical resources. How...

Artificial intelligence in detecting dentomaxillofacial fractures in diagnostic imaging: a scoping review protocol.

INTRODUCTION: The dentomaxillofacial (DMF) area, which includes the teeth, maxilla, mandible, zygomaticum, orbits and midface, plays a crucial role in...

Identification of Child Survivors of Sex Trafficking From Electronic Health Records: An Artificial Intelligence Guided Approach.

Survivors of child sex trafficking (SCST) experience high rates of adverse health outcomes. Amidst the duration of their victimization, survivors regu...

APPRAISE-HRI: AN ARTIFICIAL INTELLIGENCE ALGORITHM FOR TRIAGE OF HEMORRHAGE CASUALTIES.

Background: Hemorrhage remains the leading cause of death on the battlefield. This study aims to assess the ability of an artificial intelligence tria...

Pulmonary contusion: automated deep learning-based quantitative visualization.

PURPOSE: Rapid automated CT volumetry of pulmonary contusion may predict progression to Acute Respiratory Distress Syndrome (ARDS) and help guide earl...

Intrusive Traumatic Re-Experiencing Domain: Functional Connectivity Feature Classification by the ENIGMA PTSD Consortium.

BACKGROUND: Intrusive traumatic re-experiencing domain (ITRED) was recently introduced as a novel perspective on posttraumatic psychopathology, propos...

Using Deep Learning to Detect the Presence and Location of Hemoperitoneum on the Focused Assessment with Sonography in Trauma (FAST) Examination in Adults.

Abdominal ultrasonography has become an integral component of the evaluation of trauma patients. Internal hemorrhage can be rapidly diagnosed by findi...

Robot Assisted Laparoscopy Combined with Thoracoscopy in the Treatment of Hepatocellular Carcinoma with Inferior Vena Cava Tumor Thrombus.

BACKGROUND: Facing the 0.7-22% incidence rate of hepatocellular carcinoma (HCC) with inferior vena cava tumor thrombus (IVCTT), there are usually no o...

[Application of artificial intelligence systems in the emergency room : Do the communication patterns give indications for possible starting points? An observational study].

BACKGROUND: High expectations are currently attached to the application of artificial intelligence (AI) in the resuscitation room treatment of trauma ...

Development of a Deep Learning Model for Retinal Hemorrhage Detection on Head Computed Tomography in Young Children.

IMPORTANCE: Abusive head trauma (AHT) in children is often missed in medical encounters, and retinal hemorrhage (RH) is considered strong evidence for...

Effects of da Vinci robot versus thoracoscopic surgery on body trauma and lymphocyte subsets in lung cancer patients: A propensity score matching study.

BACKGROUND: To assess the impact of da Vinci robot versus thoracoscopic surgery on body trauma and lymphocyte subsets in lung cancer patients.

Henry gas solubility optimization double machine learning classifier for neurosurgical patients.

This study aims to predict head trauma outcome for Neurosurgical patients in children, adults, and elderly people. As Machine Learning (ML) algorithms...

CG02N Analyzer Accurately Measures Fibrinogen Level in Whole Blood in the Presence of Low- or High-Dose Heparin.

Rapid fibrinogen (Fbg) evaluation is important in patients with massive bleeding during severe trauma and those undergoing major surgery. However, the...

The three-dimensional weakly supervised deep learning algorithm for traumatic splenic injury detection and sequential localization: an experimental study.

BACKGROUND: Splenic injury is the most common solid visceral injury in blunt abdominal trauma, and high-resolution abdominal computed tomography (CT) ...

FAST skill assessment from kinematics data using convolutional neural networks.

PURPOSE: FAST is a point of care ultrasound study that evaluates for the presence of free fluid, typically hemoperitoneum in trauma patients. FAST is ...