Staffing & Scheduling

Comprehensive recommendations for the implementation of artificial intelligence in healthcare: a narrative review on facilitators and barriers.

OBJECTIVES: The integration of artificial intelligence (AI) technologies into clinical practice holds significant promise for enhancing healthcare delivery, yet substantial barriers remain to their widespread adoption. This narrative review aimed, first, to identify key facilitators and barriers to the implementation of AI technologies in patient care, and, second, to introduce a comprehensive lis...

A continual learning framework with long-term and multiple short-term memory networks.

Continual learning aims to sequentially accumulate knowledge while balancing stability and plasticity. Most existing methods focus on mitigating catastrophic forgetting, often at the expense of plasticity. While incorporating an auxiliary memory component to focus on new task data proves effective for enhancing plasticity, using a single network to achieve this may be insufficient to capture the f...

A systematic review of efforts to predict day of surgery cancellation.

BACKGROUND: Day of surgery cancellation (DOSC) for elective surgery occurs in 18% of elective surgeries worldwide with resultant impacts on patients a...

Integrative computational and experimental identification of marine bacterial acetylcholinesterase inhibitors against alzheimer's disease.

Alzheimer's disease (AD) is a powerful neurodegenerative disease characterized by cholinergic deficiency, where the inhibition of acetylcholinesterase...

Flexible Coupling of Synaptic and Intrinsic Plasticity in a Cerebellar Circuit.

It is increasingly recognized that learning and memory depend, not only on changes in synaptic strength, but also on experience-dependent modification...

Applied immunoinformatics in modern vaccine design: a comprehensive review of available computational tools.

The rapid evolution of computational biology has transformed vaccine design from a largely empirical process into a rational, data-driven discipline. ...

A coupling network for brain computing: E-I balanced embedding in dual-attractor dynamics systems.

As an important neural network model, the continuous attractor neural network (CANN) demonstrates unique advantages in simulating and explaining the r...

Deep reinforcement learning for carrier-based aircraft flight deck operations scheduling problem.

Flight deck operations scheduling is an NP-hard combinatorial optimization problem, where traditional methods face a critical trade-off between comput...

Enhanced Identification of Chronic Ankle Instability Under Different Conditions: A New Evaluation Framework Based on Feature Fusion and Machine Learning.

This study proposed a synergy-informed evaluation framework that integrates muscle synergy features derived from non-negative matrix factorization (NN...

Attribution Explanations for Deep Neural Networks: A Theoretical Perspective.

Attribution explanation is a typical approach for interpreting deep neural networks (DNNs), aiming to quantify the contribution score of individual in...

The SEWAbility system: a video-based job analysis framework for understanding task-specific job demands.

This study introduces the Smart Evaluation of Work Ability (SEWAbility), an AI-powered video analysis system designed to support objective job analysi...

Edge computing task scheduling mechanism based on multi-dimensional feature extraction and attention fusion.

In the edge computing environment, when existing task scheduling algorithms allocate resources for tasks, the central host of edge computing consumes ...

Hierarchical Channeled Graphitized Nanoarchitecture as a Diagnostic Platform for Maternal Fever Warning.

The precision and effectiveness of nano-diagnostic platforms rely on the deliberate design of advanced nanomaterials, aiming to address the clinical c...

A comprehensive review of non-destructive technologies for banana ripeness assessment: implications for food quality, safety, and supply chain management.

Banana (Musa spp.) is a primary climacteric fruit characterized by a rapid surge in ethylene production and respiration post-harvest. Accurate ripenes...

Rapid response teams for new leaders: a narrative review of global evidence and implementation strategies with a focus on Japan.

BACKGROUND: Rapid response systems (RRSs) are designed to detect and treat physiological deterioration before cardiac arrest occurs. Since 2020, Japan...

A semi-supervised domain adaptation framework with attention-enhanced ResNet50 for LIBS-based soil classification under spectral distribution shift.

BACKGROUND: Laser-induced breakdown spectroscopy (LIBS), as a rapid and non-destructive analytical technique, has been widely applied in soil classifi...

Achieving Optimal Accuracy and Robustness Through Tight Excitatory-Inhibitory Balance in Shallow Spiking Recurrent Neural Network.

Traditional deep neural networks exhibit high computational complexity during training and lack biological interpretability due to their reliance on b...

A minimal recurrent neural network models the robustness of interleaved practice on motor sequence learning.

Effective motor skill learning depends critically on the structure of practice, not solely on practice volume. This study explores the differential le...

Predictors and Perceptions of mHealth App Engagement in Older Adults: A Mixed-Methods Study on Nurse-Supported Interventions.

OBJECTIVES: To examine nurse-supported interventions on sustained mobile health (mHealth) engagement and identify predictors of long-term use in commu...

Artificial intelligence and medicine: an epistemological inquiry.

Artificial intelligence (AI) in medicine inspires both enthusiasm and concern. It introduces an unprecedented development in the history of knowledge:...