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Intensive longitudinal assessment following index trauma to predict development of PTSD using machine learning.

There are significant challenges to identifying which individuals require intervention following exp...

Applications of deep learning in trauma radiology: A narrative review.

Diagnostic imaging is essential in modern trauma care for initial evaluation and identifying injurie...

YOLOX-SwinT algorithm improves the accuracy of AO/OTA classification of intertrochanteric fractures by orthopedic trauma surgeons.

PURPOSE: Intertrochanteric fracture (ITF) classification is crucial for surgical decision-making. Ho...

Postoperative leukocyte counts as a surrogate for surgical stress response in matched robot- and video-assisted thoracoscopic surgery cohorts of patients: A preliminary report.

The objective is to preliminary evaluated postoperative leukocyte counts as a surrogate for the surg...

[Orthopedics and trauma surgery in the digital age].

BACKGROUND: Digital transformation is shaping the future of orthopedics and trauma surgery. Telemedi...

Deep Learning for Automated Detection and Localization of Traumatic Abdominal Solid Organ Injuries on CT Scans.

Computed tomography (CT) is the most commonly used diagnostic modality for blunt abdominal trauma (B...

Machine learning in the prediction of massive transfusion in trauma: a retrospective analysis as a proof-of-concept.

PURPOSE: Early administration and protocolization of massive hemorrhage protocols (MHP) has been ass...

A review on artificial intelligence for the diagnosis of fractures in facial trauma imaging.

Patients with facial trauma may suffer from injuries such as broken bones, bleeding, swelling, bruis...

Letter re: "Real-Time Automated Machine Learning Algorithm for Predicting Mortality in Trauma Patients: Survey Says It's Ready for Prime Time".

A method of bedside urethrography before catheterization in pelvic trauma in Korea: a case report.

We introduce a convenient method of urethrography before catheterization for patients with pelvic tr...

Utility of an Artificial Intelligence Language Model for Post-Operative Patient Instructions Following Facial Trauma.

STUDY DESIGN: Qualitative Descriptive Study.

Automatic segmentation of inconstant fractured fragments for tibia/fibula from CT images using deep learning.

Orthopaedic surgeons need to correctly identify bone fragments using 2D/3D CT images before trauma s...

An extended focused assessment with sonography in trauma ultrasound tissue-mimicking phantom for developing automated diagnostic technologies.

Medical imaging-based triage is critical for ensuring medical treatment is timely and prioritized. ...

Assessing optimal methods for transferring machine learning models to low-volume and imbalanced clinical datasets: experiences from predicting outcomes of Danish trauma patients.

INTRODUCTION: Accurately predicting patient outcomes is crucial for improving healthcare delivery, b...

Application possibilities of artificial intelligence in facial vascularized composite allotransplantation-a narrative review.

Facial vascularized composite allotransplantation (FVCA) is an emerging field of reconstructive surg...

A Real-Time Automated Machine Learning Algorithm for Predicting Mortality in Trauma Patients: Survey Says it's Ready for Prime-Time.

BACKGROUND: Though artificial intelligence ("AI") has been increasingly applied to patient care, man...

Mangled extremity: limb salvage for reconstruction versus primary amputation.

PURPOSE OF REVIEW: While MESS has historically influenced limb salvage versus amputation decisions, ...

Deep Learning Approach for Differentiating Etiologies of Pediatric Retinal Hemorrhages: A Multicenter Study.

Retinal hemorrhages in pediatric patients can be a diagnostic challenge for ophthalmologists. These ...

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 ...

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 tra...

Enhancing the clinical relevance of haemorrhage prediction models in trauma.