Sexual Assault

Machine learning prediction of footwear slip resistance on glycerol-contaminated surfaces: A pilot study.

Slippery surfaces due to oil spills pose a significant risk in various environments, including industrial workplaces, kitchens, garages, and outdoor areas. These situations can lead to accidents and falls, resulting in injuries that range from minor bruises to severe fractures or head trauma. To mitigate such risks, the use of slip resistant footwear plays a crucial role. In this study, we aimed t...

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 (BAT), significantly influencing management approaches. Deep learning models (DLMs) have shown great promise in enhancing various aspects of clinical practice. There is limited literature available on the use of DLMs specifically for trauma image evaluation. In this study, we developed a DLM aimed at ...

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 associated with decreases in mortality, multiorgan sy...

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, bruising, lacerations, burns, and deformity in the face...

Analysis of the Screw Accuracy and Postoperative Efficacy of Screw Placement in Single Position and Bipedal Position in Robot-Assisted Oblique Lumbar Interbody Fusion: Preliminary Results of Mazor X Stealth Usage.

OBJECTIVE: Traditional manual OLIF combined with pedicle screw implantation has many problems of manual percutaneous screw implantation, such as high ...

Expanding Robotic-Assisted Surgery in Gynecology Using the Potential of an Advanced Robotic System.

Minimally invasive surgery (MIS) in gynecology was introduced to achieve the same surgical objectives as traditional open surgery while minimizing tra...

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

Development and optimization of AI algorithms for wrist fracture detection in children using a freely available dataset.

INTRODUCTION: In the field of pediatric trauma computer-aided detection (CADe) and computer-aided diagnosis (CADx) systems have emerged offering a pro...

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 trauma that can be used in a resuscitation area. A 1...

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

STUDY DESIGN: Qualitative Descriptive Study.

Robot-Assisted Transcanal Endoscopic Ear Surgery for Congenital Cholesteatoma.

Congenital cholesteatoma accounts for 25% of cholesteatoma cases in children. Transcanal Endoscopic Ear Surgery (TEES) is ideal for these patients bec...

Automated detection and segmentation of pleural effusion on ultrasound images using an Attention U-net.

BACKGROUND: Ultrasonic for detecting and evaluating pleural effusion is an essential part of the Extended Focused Assessment with Sonography in Trauma...

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 surgery. Advances in deep learning technology provi...

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. However, without proper image collection and inter...

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, but large-scale risk prediction models are often de...

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

Facial vascularized composite allotransplantation (FVCA) is an emerging field of reconstructive surgery that represents a dogmatic shift in the surgic...

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, many of these predictive models are retrospective and...

Mangled extremity: limb salvage for reconstruction versus primary amputation.

PURPOSE OF REVIEW: While MESS has historically influenced limb salvage versus amputation decisions, its universal applicability remains uncertain. Wit...

[The Swecrit Biobank, associated clinical registries, and machine learning (artificial intelligence) improve critical care knowledge].

The unique Swecrit Biobank and its associated clinical registries for sepsis, ARDS, cardiac arrest, trauma, and COVID-19 include more than 150,000 blo...

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 hemorrhages can occur due to various underlying et...