Emergency Medicine

Exponentially Weighted Instance-Aware Repeat Factor Sampling for Long-Tailed Object Detection Model Training in Unmanned Aerial Vehicles Surveillance Scenarios

Object detection models often struggle with class imbalance, where rare categories appear significantly less frequently than common ones. Existing sampling-based rebalancing strategies, such as Repeat Factor Sampling (RFS) and Instance-Aware Repeat Factor Sampling (IRFS), mitigate this issue by adjusting sample frequencies based on image and instance counts. However, these methods are based on l...

3D Convolutional Neural Networks for Improved Detection of Intracranial bleeding in CT Imaging

Background: Intracranial bleeding (IB) is a life-threatening condition caused by traumatic brain injuries, including epidural, subdural, subarachnoid, and intraparenchymal hemorrhages. Rapid and accurate detection is crucial to prevent severe complications. Traditional imaging can be slow and prone to variability, especially in high-pressure scenarios. Artificial Intelligence (AI) provides a sol...

Exploring the Efficacy of Partial Denoising Using Bit Plane Slicing for Enhanced Fracture Identification: A Comparative Study of Deep Learning-Based Approaches and Handcrafted Feature Extraction Techniques

Computer vision has transformed medical diagnosis, treatment, and research through advanced image processing and machine learning techniques. Fractu...

Lie Detector: Unified Backdoor Detection via Cross-Examination Framework

Institutions with limited data and computing resources often outsource model training to third-party providers in a semi-honest setting, assuming ad...

Impact of pH and chloride content on the biodegradation of magnesium alloys for medical implants: An in vitro and phase-field study

The individual contributions of pH and chloride concentration to the corrosion kinetics of bioabsorbable magnesium (Mg) alloys remain unresolved des...

Test-Time Backdoor Detection for Object Detection Models

Object detection models are vulnerable to backdoor attacks, where attackers poison a small subset of training samples by embedding a predefined trig...

Language-based Image Colorization: A Benchmark and Beyond

Image colorization aims to bring colors back to grayscale images. Automatic image colorization methods, which requires no additional guidance, strug...

Validating Emergency Department Admission Predictions Based on Local Data Through MIMIC-IV

The effective management of Emergency Department (ED) overcrowding is essential for improving patient outcomes and optimizing healthcare resource al...

Bitcoin Burn Addresses: Unveiling the Permanent Losses and Their Underlying Causes

Bitcoin burn addresses are addresses where bitcoins can be sent but never retrieved, resulting in the permanent loss of those coins. Given Bitcoin's...

The Impact of Artificial Intelligence on Emergency Medicine: A Review of Recent Advances

Artificial Intelligence (AI) is revolutionizing emergency medicine by enhancing diagnostic processes and improving patient outcomes. This article pr...

MAP: Evaluation and Multi-Agent Enhancement of Large Language Models for Inpatient Pathways

Inpatient pathways demand complex clinical decision-making based on comprehensive patient information, posing critical challenges for clinicians. De...

Optimization-Augmented Machine Learning for Vehicle Operations in Emergency Medical Services

Minimizing response times to meet legal requirements and serve patients in a timely manner is crucial for Emergency Medical Service (EMS) systems. A...

Optimizing Large Language Models for Detecting Symptoms of Comorbid Depression or Anxiety in Chronic Diseases: Insights from Patient Messages

Patients with diabetes are at increased risk of comorbid depression or anxiety, complicating their management. This study evaluated the performance ...

Vision Transformer for Intracranial Hemorrhage Classification in CT Scans Using an Entropy-Aware Fuzzy Integral Strategy for Adaptive Scan-Level Decision Fusion

Intracranial hemorrhage (ICH) is a critical medical emergency caused by the rupture of cerebral blood vessels, leading to internal bleeding within t...

Machine learning for triage of strokes with large vessel occlusion using photoplethysmography biomarkers

Objective. Large vessel occlusion (LVO) stroke presents a major challenge in clinical practice due to the potential for poor outcomes with delayed t...

HealthiVert-GAN: A Novel Framework of Pseudo-Healthy Vertebral Image Synthesis for Interpretable Compression Fracture Grading

Osteoporotic vertebral compression fractures (VCFs) are prevalent in the elderly population, typically assessed on computed tomography (CT) scans by...

Two-Stream Thermal Imaging Fusion for Enhanced Time of Birth Detection in Neonatal Care

Around 10% of newborns require some help to initiate breathing, and 5\% need ventilation assistance. Accurate Time of Birth (ToB) documentation is e...

UAV-VLRR: Vision-Language Informed NMPC for Rapid Response in UAV Search and Rescue

Emergency search and rescue (SAR) operations often require rapid and precise target identification in complex environments where traditional manual ...

Applying Conformal Prediction to a Deep Learning Model for Intracranial Hemorrhage Detection to Improve Trustworthiness.

Purpose To apply conformal prediction to a deep learning (DL) model for intracranial hemorrhage (ICH) detection and evaluate model performance in dete...

A Deep Learning Model for Three-Dimensional Determination of Whole Thoracic Vertebral Bone Mineral Density from Noncontrast Chest CT: The Multi-Ethnic Study of Atherosclerosis.

Background Recent studies have investigated how deep learning (DL) algorithms applied to CT using two-dimensional (2D) segmentation (sagittal or axial...