Staffing & Scheduling

The Effect of Age, Sex, and Body Mass Index on Spinopelvic Balance Throughout Childhood and Adolescence: An Automated 3D-Computed Tomography Study of 9,721 Pediatric Patients.

BACKGROUND: Spinopelvic assessment is critical for surgical planning. It is unknown if age, sex, and body mass index (BMI) influence pelvic orientation during development. This study aimed to (1) describe normative pelvic orientation and (2) investigate how patient-specific factors influence pelvic orientation throughout development from childhood to early adulthood. METHODS: Computed tomography p...

Online surveys, a breakthrough in research, especially in nutrition and food sciences.

BACKGROUND: Technological advancements and widespread internet connectivity have fundamentally transformed data collection across academic disciplines. Traditional methods are increasingly being replaced by online surveys, driven by their capacity for rapid deployment, lower costs, flexible design, and automated data handling. METHODS: This narrative review synthesises methodological evidence on o...

Towards Artificial Intelligence Hardware With 3D Integrated Ferroelectric Transistors.

The increasing energy and bandwidth demand of modern AI workloads highlight the need for hardware that mitigates the data-movement bottleneck of von N...

IPEM Topical Report: A National Survey of MRI Use for External Beam Radiotherapy Treatment Planning in the UK: 2025 IPEM Survey Results.

Magnetic Resonance Imaging (MRI) offers superior soft tissue contrast compared to Computed Tomography (CT), making it highly valuable in external beam...

Predicting Somatization Risk Among Infectious Disease Disaster Frontline Nurses Using Machine Learning.

This study aimed to identify key risk factors associated with high-somatization risk among frontline nurses responding to infectious diseases, utilizi...

LLM-enabled adaptive scheduling in IoT sensing for optimized network performance.

The use of numerous sensors on edge devices, combined with the emergence of AI techniques, makes the IoT environment more intelligent and interactive....

SCMEO-DETR provides a lightweight and high efficiency solution for PCB defect detection based on RT-DETR.

Printed Circuit Board (PCB) defect detection is essential for ensuring reliability in electronic manufacturing, as defects such as spur, mouse bites, ...

TCMNet: dynamic tanh enhanced 3D transformer with cascaded multiplicative fusion for pulmonary nodule detection.

Early detection of pulmonary nodules plays a critical role in improving the survival rate of patients with lung cancer. However, existing detection me...

Artificial intelligence for monitoring hand hygiene compliance in healthcare settings: A scoping review.

BACKGROUND: Hand hygiene is a fundamental measure for preventing healthcare-associated infections, yet traditional monitoring methods are significantl...

Comparison of AI-assisted and human-produced podcasts derived from Cochrane Plain Language Summaries: protocol for a randomised non-inferiority trial (Health Information Effectiveness Trials-2).

BACKGROUND AND OBJECTIVES: Podcasts can make health evidence easier to follow, but it is unclear whether artificial intelligence (AI)-assisted product...

Equity, diversity, and inclusion: variations in clinical and academic radiology.

Equity, diversity, and inclusion (EDI) are fundamental to achieving fairness and representation in radiological research and practice. This review aim...

Popular Online Content as a Treatment-as-Usual Control in Digital Mental Health Intervention Trials: Secondary Analysis of Two Online Randomized Controlled Trials With Repeated Measures.

BACKGROUND: Treatment-as-usual (TAU) conditions are intended to reflect the support typically received in routine treatment settings. For digital ment...

Predicting future cognitive impairment in preclinical Alzheimer's disease using amyloid PET and MRI: A multisite machine learning study.

Predicting the likelihood of developing Alzheimer's disease (AD) dementia in at-risk individuals is important for the design of and optimal recruitmen...

Machine learning-driven screening of characteristic flavor markers: Investigating the impact of pulsed electric fields on the flavor profile of virgin olive oil.

Pulsed electric field (PEF) technology enhances the extraction efficiency of virgin olive oil (VOO), yet its systematic impact on the dynamic evolutio...

GRaph-based analysis for stroke prediction (GRASP): A multi-modal model for identifying first ischemic stroke in high-risk population using UK biobank.

BACKGROUND: Ischemic stroke accounts for 3.71 million deaths annually worldwide. Yet current risk prediction models demonstrate modest discrimination ...

Augmented Reality in Vocal Technique Training: Interactive Visualizations of Breath and Posture Control Using Magic Keys AR.

This study aimed to evaluate the effectiveness of Magic Keys AR as a tool for accelerating vocal learning through synchronized monitoring of breathing...

Enhancing smart factory performance via hybrid scheduling and intelligent resource management.

The rise of connected devices since the industrial revolution has led to vast data generation and new digital challenges. A huge data from smart asset...

Training in diagnostic and interventional endoscopic ultrasound: a state-of-the-art review.

INTRODUCTION: Endoscopic ultrasound (EUS) has progressed from a primarily diagnostic modality to an essential diagnostic and therapeutic platform. The...

Intelligent scheduling and resource allocation for urban air mobility networks based on graph neural networks.

Generalization of Left Ventricular Segmentation Models to LVNC Patients: A Comparative Study.

Left ventricular non-compaction (LVNC) is a rare cardiomyopathy with distinctive myocardial morphology. Due to its low prevalence, LVNC cases are rare...