Staffing & Scheduling

Domain shift analysis of deep learning models for tooth detection in pediatric panoramic radiographs.

The aim of this study was to externally validate object detection models for comprehensive tooth detection on pediatric panoramic radiographs, quantify the impact of domain shift across institutions and imaging protocols, and compare YOLOv8 and YOLOv10. Two datasets were used: an internal set of 200 images of early mixed dentition without bite blocks, and an external, open-source set of 192 images...

Optimizing land use and land cover classification with deep learning on multi-resolution datasets.

Land use and land cover (LULC) classification is essential for environmental monitoring, urban planning, and resource management. This study explores the performance of three state-of-the-art deep learning architectures, MobileNetV3, ResNet34, and GoogleNet, which were enhanced with transfer learning, data augmentation, and adaptive learning rate scheduling. We evaluate these models on two benchma...

Template-Based Label Propagation for Mouse Brain MRI Skull Stripping.

Accurate skull stripping is an essential preprocessing step in mouse brain magnetic resonance imaging, particularly for reliable atlas registration an...

Evaluation of artificial intelligence generated immersive virtual reality simulation on skill mastery.

BACKGROUND: Nursing education faces challenges in providing nursing students with sufficient clinical site opportunities due to healthcare staffing sh...

A NETs-centric multi-omics framework prioritizes PGLYRP1 and MMP9 as subtype-associated thromboinflammatory biomarker candidates and putative therapeutic hypotheses in ischemic stroke.

Neutrophil extracellular traps are implicated in immunothrombosis and neuroinflammation in ischemic stroke, but blood-based markers that distinguish s...

Artificial intelligence-driven early screening and diagnosis of pancreatic cancer: technical innovations, clinical applications, and precision medicine strategies.

BACKGROUND: Pancreatic cancer is characterized by prolonged subclinical progression, molecular heterogeneity, and late clinical presentation, resultin...

When brand prominence mutes uniqueness: Deconstructing the prominence paradox with network science and machine learning.

This study investigates the "Prominence Paradox": how market prominence paradoxically suppresses brand uniqueness signals. Grounded in dual-process th...

Integrating explainable AI and multi-objective optimization for wildfire resource allocation under fixed staffing constraints: a decision-oriented framework.

The impact of scanner domain shift on deep learning performance in medical imaging: an experimental study.

PURPOSE: Medical images acquired using different scanners and protocols can differ substantially in their appearance. This phenomenon, scanner domain ...

[Pit and fissure morphology and its implication for caries prevention and treatment].

Dental caries is a chronic and progressive destruction of dental hard tissue under the combined action of multiple factors, with the pits and fissures...

Research on the generalization of a blood donor recruitment framework based on machine learning.

Increased Endurance of Nonvolatile Photonics Enabled by Nanostructured Phase-Change Materials.

The rapid rise of artificial intelligence, and in-memory computing has reinvigorated research on scalable, energy-efficient, and reconfigurable photon...

Impracticality of banning collection of data on ethnicity and race in artificial intelligence-enabled health care in France.

Artificial intelligence (AI) or machine learning (ML) are revolutionising health care, enhancing diagnostics and treatment through AI-enabled medical ...

Recurrent Processing Dynamics in Occluded Object Recognition Revealed by Electroencephalography and Deep Neural Networks.

The human visual system excels at recognizing occluded objects, yet the temporal dynamics of recurrent processing in this task remain unclear. Using h...

SPACESHIP: Autonomous Mapping of Hardware-Dependent Synthesizable Space in Solution-Phase Gold Nanomaterials.

Autonomous laboratories hold great promise for accelerating materials discovery but often inherit hidden limits because experimental boundaries have b...

Image-Based Deep Learning for Cataract Diagnosis: Systematic Review and Meta-Analysis.

BACKGROUND: Cataracts are an eye condition characterized by high prevalence and blindness-inducing potential, and effective approaches are required fo...

Clinical AI is Not (Yet) Trustworthy-But It Could Be.

The growing emphasis on trustworthy artificial intelligence (AI) in health care reflects a shift away from models optimized for predictive performance...

Hybrid ML-driven simulation exploring the fate of environmentally relevant nanoplastics in complex aqueous matrices: Mechanistic insight into colloidal behavior via explainable AI.

Nanoplastics (NPs) are globally recognized as pervasive emerging contaminants with demonstrated toxicological risks, yet predicting their environmenta...

Green artificial intelligence in health applications.

As the healthcare sector increasingly integrates Artificial Intelligence (AI) technologies to improve operational effectiveness, diagnosis, and therap...

Open access and digital morphology data in evolutionary biology: expanding frontiers of knowledge.

The recent integration of 3D imaging and digital methodologies has revolutionized evolutionary biology, offering unprecedented opportunities for analy...