Sexual Assault

Deep Learning for Ultrasound-Based Auxiliary Diagnosis of Emergency Ascites.

OBJECTIVE: The Focused Assessment with Sonography for Trauma (FAST) enables rapid detection of free intraperitoneal fluid, facilitating timely management of internal hemorrhage. This study aims to develop a Transformer-based model for automated detection on FAST images and evaluate its feasibility in assisting non-specialist operators. METHODS: Between June 2019 and June 2024, 1829 FAST-positive i...

A CT-based multimodal fusion model for predicting outcomes in blunt chest trauma: A multicenter study.

BACKGROUND: This study aimed to develop a multimodal predictive model that integrates clinical variables, radiomic features (RFs), and deep learning-based features (DLFs) to improve prognostic accuracy in patients with blunt chest trauma (BCT). METHODS: We retrospectively analyzed 337 patients with BCT from three medical centers. Clinical and CT imaging data, including emergency and follow-up scan...

Automated detection and classification of dental trauma in periapical radiographs using deep learning: a study based on the Andreasen classification.

OBJECTIVE: The aim of this study was to evaluate the performance of a deep learning (DL) model in automatically identifying dental trauma types on sel...

Development and validation of machine learning models to predict PTSD at multiple time points in hospitalized trauma patients.

BACKGROUND: Posttraumatic stress disorder (PTSD) is a severe trauma-related mental disorder with high global burden. Early identification remains chal...

Improving Acute Care Surgery with Artificial Intelligence: A Practical Review.

Artificial intelligence (AI) and machine learning are poised to transform trauma care across the entire continuum, from prehospital triage to postoper...

SOS Dental Trauma-An Artificial Intelligence Chatbot via WhatsApp for Guiding Patients After Dental Trauma.

BACKGROUND: Traumatic dental injuries (TDIs) are highly prevalent worldwide and require immediate and appropriate management to ensure favorable outco...

Can Artificial Intelligence and Machine Learning help us improve motor vehicle crash trauma triage?

Ensemble machine learning for early mortality risk stratification in septic orthopedic trauma: an international cohort study.

BACKGROUND: Sepsis represents a life-threatening complication in severe orthopedic trauma, significantly increasing short-term mortality risk. Despite...

Industry 6.0 capabilities in orthopaedics: Towards hyper-personalized and autonomous surgical care.

BACKGROUND: Industry 6.0 represents the next frontier in technological evolution, integrating artificial intelligence (AI), autonomous robotics, digit...

Generative artificial intelligence provides accurate case selection in veterinary retrospective studies.

OBJECTIVE: To evaluate the agreement of automation tools with expert evaluators in identifying cases meeting inclusion and exclusion criteria for retr...

Computer-vision based recognition of cervical spine stabilization during trauma resuscitation.

BACKGROUND: Cervical spine (c-spine) injuries can lead to significant disability and mortality. Although stabilization is the primary management for s...

Quantitative EEG enhances early assessment and prognostic stratification of brain dysfunction in infants with abusive head trauma.

AIM: To assess the value of quantitative EEG (qEEG) as a diagnostic and prognostic biomarker in infants with abusive head trauma (AHT). Despite its ce...

Persistent dysmorphology and dysfunction of the brain microvasculature following repeated trauma.

Mild traumatic brain injury typically produces no abnormalities on neuroimaging yet elicits symptoms that, in an increasing fraction of survivors, lin...

Performance Comparison of a Domain-Specific Chatbot and General-Purpose Chatbots in Dental Traumatology.

BACKGROUND: Use of artificial intelligence chatbots in dental traumatology has increased. However, concerns regarding their reliability are yet to be ...

Comparative Performance of YOLO Models in the Automated Segmentation of Dental Traumas on Panoramic Radiographs.

OBJECTIVE: This study aimed to compare the performance of artificial intelligence-based deep convolutional neural networks, YOLOv8, YOLOv11, and YOLOv...

An Algorithm to Avoid Missed Bowel Injuries in Blunt Abdominal Trauma Patients.

UNLABELLED: Bowel injuries following blunt abdominal trauma (BAT) are evasive to detect clinically and with current imaging modalities. These injuries...

Machine learning identifies traumatic experiences as being associated with auditory verbal hallucinations in both a non-clinical population and individuals diagnosed with psychosis.

BACKGROUND: Auditory verbal hallucinations (AVHs) are a core symptom of psychosis but their prevalence in the general population ranges from 5-28 %. M...

Ultrasound to guide critical decisions: What you need to know.

BACKGROUND: Hypotension in the intensive care unit (ICU) demands rapid diagnosis and intervention, as delays in identifying the etiology of shock dire...

Precision medicine in orthopaedics: A review of current technologies and future directions.

PURPOSE: To synthesise the paradigm shift towards precision medicine in orthopaedics, where individual anatomical, biomechanical, molecular and kinema...

From static to robotic: evolving navigation systems in oral and maxillofacial surgery.

Navigation-assisted surgical systems in oral and maxillofacial surgery have evolved considerably over the past 5 years, with newer modifications aimed...