Sexual Assault

An integrated analytical framework for gender-based violence research: A simulation study combining machine learning and causal inference

Current research on Gender-Based Violence (GBV) typically separates predictive machine learning and causal inference into distinct analytical silos. Yet, grasping the multi-level determinants of violence requires an approach that can both identify high-value predictors and disentangle their causal mechanisms. This study develops and validates an integrated five-phase analytical framework to demons...

Intimate partner violence and stress-related disorders: from epigenomics to resilience.

Intimate Partner Violence (IPV) is a major public health problem to be addressed with innovative and interconnecting strategies for ensuring the psychophysical health of the surviving woman. According to the World Health Organization, 27% of women worldwide have experienced physical and sexual IPV in their lifetime. Most of the studies on gender-based violence focus on short-term effects, while lo...

SCIseg: Automatic Segmentation of Intramedullary Lesions in Spinal Cord Injury on T2-weighted MRI Scans.

Purpose To develop a deep learning tool for the automatic segmentation of the spinal cord and intramedullary lesions in spinal cord injury (SCI) on T2...

RSNA 2023 Abdominal Trauma AI Challenge: Review and Outcomes.

Purpose To evaluate the performance of the winning machine learning models from the 2023 RSNA Abdominal Trauma Detection AI Challenge. Materials and M...

Is Generative AI Increasing the Risk for Technology-Mediated Trauma Among Vulnerable Populations?

The proliferation of Generative Artificial Intelligence (Generative AI) has led to an increased reliance on AI-generated content for designing and dep...

If Eleanor Rigby Had Met ChatGPT: A Study on Loneliness in a Post-LLM World

Loneliness, or the lack of fulfilling relationships, significantly impacts a person's mental and physical well-being and is prevalent worldwide. Pre...

[Application progress and future prospects of interventional robotics in vascular injury hemostasis].

The field of traumatic hemostasis is currently confronted with numerous challenges, particularly in addressing the treatment of non-compressible torso...

Development of machine learning prediction model for AKI after craniotomy and evacuation of hematoma in craniocerebral trauma.

The aim of this study was to develop a machine-learning prediction model for AKI after craniotomy and evacuation of hematoma in craniocerebral trauma....

Learning from the few: Fine-grained approach to pediatric wrist pathology recognition on a limited dataset

Wrist pathologies, {particularly fractures common among children and adolescents}, present a critical diagnostic challenge. While X-ray imaging rema...

Remote Monitoring, AI, Machine Learning and Mobile Ultrasound Integration upon 5G Internet in the Prehospital Care to Support the Golden Hour Principle and Optimize Outcomes in Severe Trauma and Emergency Surgery.

AIM: Feasibility and reliability evaluation of 5G internet networks (5G IN) upon Artificial Intelligence (AI)/Machine Learning (ML), of telemonitoring...

Prediction of Occult Hemorrhage in the Lower Body Negative Pressure Model: Initial Validation of Machine Learning Approaches.

INTRODUCTION: Detection of occult hemorrhage (OH) before progression to clinically apparent changes in vital signs remains an important clinical probl...

DP2LM: leveraging deep learning approach for estimation and hypothesis testing on mediation effects with high-dimensional mediators and complex confounders.

Traditional linear mediation analysis has inherent limitations when it comes to handling high-dimensional mediators. Particularly, accurately estimati...

Embedded Force Sensor with Deep Transformation Calibration for Interventional Soft Robots.

A calibration method for gelatin-graphite-based soft sensors is proposed. This approach uses convolutional deep learning approaches that account for a...

Acute Stress Disorder Detection using Machine Learning based on resting-state fMRI.

Early diagnosis of Acute Stress Disorder (ASD) is important, given its potential progression to post-traumatic system disorder (PTSD). The current dia...

Prediction of gait recovery using machine learning algorithms in patients with spinal cord injury.

With advances in artificial intelligence, machine learning (ML) has been widely applied to predict functional outcomes in clinical medicine. However, ...

Deep-Learning Approach for Tissue Classification using Acoustic Waves during Ablation with an Er:YAG Laser (Updated)

Today's mechanical tools for bone cutting (osteotomy) cause mechanical trauma that prolongs the healing process. Medical device manufacturers aim to...

[Minimally invasive intelligent innovative technologies in foot and ankle surgery: development status and prospects].

The rapid development of technology has ushered in a new era of minimally invasive and intelligent surgery.Minimally invasive surgeries, such as small...

Automated stratification of trauma injury severity across multiple body regions using multi-modal, multi-class machine learning models.

OBJECTIVE: The timely stratification of trauma injury severity can enhance the quality of trauma care but it requires intense manual annotation from c...

APPLICATION OF ARTIFICIAL INTELLIGENCE IN CIVIL AND MILITARY MEDICINE.

Artificial intelligence (AI) encompasses the advancement of computers and robots, enabling them to surpass human capabilities in various aspects. By u...

[Real-time traking and virtual reality technology-assisted trauma orthopaedic surgery robot for femoral neck fractures].

OBJECTIVE: To investigate the effectiveness of real-time tracking and virtual reality technology（RTVI） used to assist the intraoperative alignment of ...