Infection Control

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 suspected c-spine injuries, lapses in stabilization frequently occur during trauma resuscitation. To facilitate evaluation of c-spine management, we developed a computer vision system to detect stabilization techniques. This system would enable scalab...

Establishment of CT diagnostic reference levels (DRLs) in Tokyo.

OBJECTIVE: Diagnostic reference levels (DRLs) are essential for optimizing radiation dose in CT examinations. However, current DRLs may not reflect the performance of CT scanners or the background of individual facilities, potentially leading to misleading dose indicators. Furthermore, the factors that influence DRLs remain unclear. This study aims to investigate how facility characteristics and C...

Machine learning models for predicting hospital admission in pediatric emergency departments: A systematic review.

CONTEXT: Pediatric Emergency Departments (PEDs) face overcrowding partially due to delayed hospital admission decision. Machine Learning (ML) models c...

Patients visits forecasting in emergency departments: Self-adapting LSTM models for evolving data distributions.

BACKGROUND AND OBJECTIVE: Overcrowding in emergency departments (EDs) remains a critical challenge in healthcare systems. Accurate forecasting of pati...

Digital Eye: Deep Learning for Detecting Physeal Fractures of the Pediatric Distal Radius.

BACKGROUND: Distal radial fractures (DRFs) are some of the most common pediatric injuries, often involving the physis. Diagnostic accuracy can be chal...

Nanomotion-based technology for rapid antibiotic susceptibility testing among adult patients admitted to a tertiary-care hospital with Gram-negative bacteraemia: a prospective, single arm, comparative diagnostic accuracy study.

OBJECTIVE: Investigate performances and turnaround time of Resistell Phenotech antibiotic susceptibility testing (AST), a device using the new nanomot...

A Window Into Vulnerability and Support: At-Risk Mothers' Perinatal Experiences and Perspectives on mHealth-Based Care.

AIM: To examine the perinatal experiences of at-risk mothers and their engagement with mobile-health-based care. DESIGN: A qualitative descriptive stu...

GPT-4o in Nutrition for Inpatients Undergoing Post-Stroke Rehabilitation: Identifying Dietary Errors, Exploring Expert-AI Rationale Differences, and Structuring AI-Expert Collaboration.

OBJECTIVE: Inpatients undergoing stroke rehabilitation experience high malnutrition rates, requiring strict dietary management. However, manual and ti...

A rural-to-center artificial intelligence model for diagnosing Helicobacter pylori infection and premalignant gastric conditions using endoscopy images captured in routine practice.

Diagnosing Helicobacter pylori infection and premalignant gastric conditions typically requires 13C urea breath testing or histological assessment, wh...

Therapeutic Drug Monitoring and Point-of-Care Technologies: Opportunities and Current Challenges.

BACKGROUND: This review re-evaluates therapeutic drug monitoring (TDM) by comparing the current analytical and subsequent clinical interpretation capa...

Smart Hospital Infrastructure: Enhancing Parking Management and Ambulance Accessibility in Urban Healthcare Systems.

Hospitals face significant challenges in parking management and assessing ambulances due to fast-growing urbanization, high population density, and tr...

Hospital waste management in Germany and the European Union during the Industry 5.0 era for carbon neutrality by 2050: A critical review.

Hospital waste management (HWM) is critical to advancing environmental sustainability, particularly as Germany and the European Union (EU) pursue carb...

Diagnostic Accuracy of a Large Language Model (ChatGPT-4) for Patients Admitted to a Community Hospital Medical Intensive Care Unit: A Retrospective Case Study.

BackgroundThe future of artificial intelligence in medicine includes the use of machine learning and large language models to improve diagnostic accur...

Machine learning-selected minimal features drive high-accuracy rule-based antibiotic susceptibility predictions for via metagenomic sequencing.

Antimicrobial resistance (AMR) represents a critical global health challenge, demanding rapid and accurate antimicrobial susceptibility testing (AST) ...

Advantages and effectiveness of AI three-dimensional reconstruction technology in the preoperative planning of total hip arthroplasty.

In order to explore the application effect of artificial intelligence (AI) 3D reconstruction technology in total hip arthroplasty (THA), this study in...

Application of Transformer Neural Networks for Data Cleaning in Emergency Room Logs: A Case Study from the Bordeaux University Hospital.

Emergency Rooms (ERs) are at the center of various optimization research due to the growing number of visits in recent decades. The accurate logging o...

Citywide metagenomic surveillance of food centres reveals local microbial signatures and antibiotic resistance gene enrichment.

The distribution of microorganisms in built environments with high human traffic, such as food centres, can potentially have a significant impact on p...

Bridging the gap between models and reality: development of a research environment for an object-oriented hospital information system to integrate artificial intelligence and robotics into clinical practice.

INTRODUCTION: Hospital information systems (HISs) are the main access opportunity for medical professionals to computer-based patient administration. ...

Machine learning for the prediction of urosepsis using electronic health record data.

Urosepsis, a medical condition resulting from the progression of urinary tract infection (UTI), is a leading cause of death in the US. Urosepsis occur...

Identifying real time surveillance indicators to estimate COVID-19 hospital admissions in Colorado during and after the public health emergency.

Questions remain about how best to focus surveillance efforts for COVID-19 and other emerging respiratory diseases. We used an archive of COVID-19 dat...