Staffing & Scheduling

EXPRESS: It's not all rapid dilations: on contributions of constrictions, biphasic and minute-long vessel responses to brain functional hyperemia.

Though neurovascular coupling has long been studied, a comprehensive characterization of the extent, kinetics, and variability of individual microvessels' responses is lacking. To address this, we employed our NOVAS3D deep learning pipeline to analyze microvascular volumes acquired in mice under alpha-chloralose sampled every ~4 s for 5 minutes before and after either somatosensory stimulation or ...

Bioactive Peptides for Oral Diseases: Biomaterial-Assisted Therapeutics and Translational Applications.

Dental caries, periodontitis, oral mucosal inflammation, peri-implant infections, and oral tissue defects remain major clinical burdens. Conventional treatments, including antimicrobials, antibiotics, anti-inflammatory agents, and regenerative materials, are frequently limited by rapid clearance from saliva-exposed oral surfaces, insufficient discrimination between pathogenic and commensal microor...

Single-cell and Spatial Transcriptomic Profiling Reveal that LAPTM5-mediated Ferroptosis in Macrophages Induces Fibroblast Dysfunction and Amplifies Periodontal Inflammation.

Periodontitis represents a persistent inflammatory condition marked by gradual damage to the gingival connective tissues and alveolar bone. Programmed...

An Edge On-Chip-Learning Convolutional Spiking Neural Network Processor Based on Error Backpropagation via Spatiotemporal Nodes of Spike Events.

While Spiking Neural Networks (SNNs) offer high energy efficiency for edge computing, implementing on-chip backpropagation for convolutional topologie...

Finding the Goldilocks Zone for Toddler Accelerometry: How Many Days Are Needed for a Reliable Estimate of Physical Activity and Sedentary Time Using Machine Learning?

PURPOSE: To understand how many days and hours per day of accelerometer wear are needed for a reliable estimation of sedentary time and physical activ...

A multimodal machine learning framework outperforms traditional performance metrics for predicting elite national ranking attainment in adolescent sprinters.

Traditional talent identification in sprinting relies heavily on chronological performance metrics, which are often confounded by biological maturatio...

Domain Generalization Mitigates Scanner-Induced Domain Shift in Medical Imaging.

Deep learning models for medical image analysis often fail in clinical deployment due to domain shift from varied acquisition hardware and protocols. ...

Virtual simulation as a catalyst for equitable and authentic interprofessional learning.

BACKGROUND: Interprofessional education (IPE) is essential for preparing health sciences students for collaborative practice, yet its implementation r...

Beyond technological affordances: Trust and continued intention to use AI-enabled recruitment systems across neurodivergent and neurotypical applicants.

This study examines how technological affordances shape applicants' continued intention to use AI-enabled recruitment systems, with particular attenti...

M-JEPA: Predictive Self-Supervised Learning for Molecular Graphs with Scaffold-Shift Evaluation on Tox21.

Self-supervised molecular representation learning can improve transfer on label-limited property prediction tasks, but contrastive objectives are sens...

Deep learning-based chemical shift-artifact correction of ZTE MRI for enhanced bone depiction of the lumbar spine.

RATIONALE AND OBJECTIVES: Zero echo time (ZTE) is an advanced MRI technique providing CT-like images of mineralized tissues. This study evaluates the ...

Precision Transfusion Medicine in the Omics Era.

Transfusion medicine has practiced a form of precision medicine for decades through compatibility testing, infectious disease screening, component man...

Artificial Intelligence-Assisted Screening for Patients With Diabetic Retinopathy and Age-Related Macular Degeneration in Family Medicine and Geriatric and Gerontology Care: Protocol for a Pragmatic Randomized Clinical Trial.

BACKGROUND: Diabetic retinopathy (DR) and age-related macular degeneration (AMD) are 2 of the leading causes of vision loss worldwide. As population a...

Implementation determinants of a planned machine learning-enabled surgical scheduling system in a high-volume orthopaedic centre in Canada: qualitative findings.

OBJECTIVES: Elective non-emergent surgical wait times have increased across countries such as Canada, straining operating room (OR) resources and affe...

Application of deep machine learning in dental education: a systematic review of effectiveness in dental students' teaching learning outcomes.

BACKGROUND: Deep machine learning (DML) technologies, including convolutional neural networks (CNN) and transformer-based models, are increasingly use...

Artificial general intelligence and the clinical laboratory: a paradigm shift toward Lab 2.0.

Clinical laboratory medicine faces converging structural pressures: workforce shortages, growing data complexity, and rapid advances in artificial int...

Diagnostic performance of machine learning models based on dual-phase 99mTc-MIBI SPECT/CT semiquantitative parameters for differentiating benign and malignant pulmonary nodules.

PURPOSE: To evaluate the diagnostic value of machine learning models based on dual-phase 99mTc-MIBI SPECT/CT semiquantitative parameters for different...

Reconfigurable 2D Floating-Gate Field-Effect Transistors with Graphene-Induced Interfacial Polarization for Unified Memory-Logic Integration.

As artificial intelligence (AI) continues to proliferate, highly integrated, energy-efficient hardware with reconfigurability is essential for advanci...

Rostral lesion shift and tract-specific degeneration drive functional heterogeneity in degenerative cervical myelopathy.

BACKGROUND: Degenerative cervical myelopathy (DCM) is the leading cause of spinal cord impairment worldwide, yet conventional magnetic resonance imagi...

Pupil-DLC: an open-source deep learning pipeline for scalable, marker-less tracking of pupil dynamics across conscious and unconscious states.

BACKGROUND: Pupil diameter is a non-invasive biomarker of brain state, correlating with arousal, attention, cognitive processing, and consciousness. H...