Staffing & Scheduling

PT-KGNN: A framework for pre-training biomedical knowledge graphs with graph neural networks.

Biomedical knowledge graphs (KGs) serve as comprehensive data repositories that contain rich informa...

Synergistic Polymer Blending Informs Efficient Terpolymer Design and Machine Learning Discerns Performance Trends for pDNA Delivery.

Cationic polymers offer an alternative to viral vectors in nucleic acid delivery. However, the devel...

Toward human-like adaptability in robotics through a retention-engineered synaptic control system.

Although advanced robots can adeptly mimic human movement and aesthetics, they are still unable to a...

Biohybrid microrobots regulate colonic cytokines and the epithelium barrier in inflammatory bowel disease.

Cytokines have been identified as key contributors to the development of inflammatory bowel disease ...

Artificial intelligence and personalized diagnostics in periodontology: A narrative review.

Periodontal diseases pose a significant global health burden, requiring early detection and personal...

Artificial intelligence in dermatology: Bridging the gap in patient care and education.

The application of artificial intelligence (AI) in education and clinical medicine has shown tremend...

Enhancing post-training evaluation of annual performance agreement training: A fusion of fsQCA and artificial neural network approach.

This study aims to enhance the post-training evaluation of the annual performance agreement (APA) tr...

Climate change and artificial intelligence in healthcare: Review and recommendations towards a sustainable future.

The rapid advancement of artificial intelligence (AI) in healthcare has revolutionized the industry,...

Self-help groups and opioid use disorder treatment: An investigation using a machine learning-assisted robust causal inference framework.

OBJECTIVES: This study investigates the impact of participation in self-help groups on treatment com...

Predictability of buprenorphine-naloxone treatment retention: A multi-site analysis combining electronic health records and machine learning.

BACKGROUND AND AIMS: Opioid use disorder (OUD) and opioid dependence lead to significant morbidity a...

Magnitude and angle dynamics in training single ReLU neurons.

Understanding the training dynamics of deep ReLU networks is a significant area of interest in deep ...

Artificial intelligence, workers, and future of work skills.

Historically, the use of technology in organizations has reshaped the nature of human work. In this ...

A novel method combining deep learning with the Kennard-Stone algorithm for training dataset selection for image-based rice seed variety identification.

BACKGROUND: Different varieties of rice vary in planting time, stress resistance, and other characte...

Validation of the identification reliability of known and assumed UDMH transformation products using gas chromatographic retention indices and machine learning.

Thirty two commercially available standards were used to determine chromatographic retention indices...

Improved Classification Performance of Bacteria in Interference Using Raman and Fourier-Transform Infrared Spectroscopy Combined with Machine Learning.

The rapid and sensitive detection of pathogenic and suspicious bioaerosols are essential for public ...

Comparing human text classification performance and explainability with large language and machine learning models using eye-tracking.

To understand the alignment between reasonings of humans and artificial intelligence (AI) models, th...

Predicting daily recovery during long-term endurance training using machine learning analysis.

PURPOSE: The aim of this study was to determine if machine learning models could predict the perceiv...

Machine Learning-Assisted Optimization of Mixed Carbon Source Compositions for High-Performance Denitrification.

Appropriate mixed carbon sources have great potential to enhance denitrification efficiency and redu...

Engaging nurses in developing generative artificial intelligence-based technologies can enhance their work motivation, engagement and satisfaction.

Applicability of machine learning techniques to analyze Microplastic transportation in open channels with different hydro-environmental factors.

This research utilized machine learning to analyze experiments conducted in an open channel laborato...

Machine learning models and performance dependency on 2D chemical descriptor space for retention time prediction of pharmaceuticals.

The predictive modeling of liquid chromatography methods can be an invaluable asset, potentially sav...