Latest AI and machine learning research in staffing & scheduling for healthcare professionals.
Fluorescence lifetime imaging (FLI) is an important technique for studying cellular environments and molecular interactions, but its real-time application is limited by slow data acquisition, which requires capturing large time-resolved images and complex post-processing using iterative fitting algorithms. Deep learning (DL) models enable real-time inference, but can be computationally demanding...
In various fields, including medicine, age distributions are crucial. Despite widespread media coverage of health topics, there remains a need to enhance health communication. Narrative medical visualization is promising for improving information comprehension and retention. This study explores the most effective ways to present age distributions of diseases through narrative visualizations. We ...
Conversational Swarm Intelligence (CSI) is an AI-powered communication and collaboration technology that allows large, networked groups (of potentia...
This paper explores the potential application of Deep Reinforcement Learning in the furniture industry. To offer a broad product portfolio, most fur...
The time-critical industrial applications pose intense demands for enabling long-distance deterministic networks. However, previous priority-based a...
With the rapid development of VR technology, the demand for high-quality 3D models is increasing. Traditional methods struggle with efficiency and q...
Deadline-aware transmission scheduling in immersive video streaming is crucial. The objective is to guarantee that at least a certain block in multi...
Knowledge Graphs (KGs) serving as semantic networks, prove highly effective in managing complex interconnected data in different domains, by offerin...
We applied natural language processing (NLP) to a corpus extracted from 4 hours of expert panel discussion transcripts to determine the sustainability...
The effective management of human resources in nursing is fundamental to ensuring high-quality care. The necessary staffing levels can be derived from...
Bayesian Neural Networks(BNNs) with high-dimensional parameters pose a challenge for posterior inference due to the multi-modality of the posterior ...
AI researchers and ethicists have long worried about the threat that automation poses to human dignity, autonomy, and to the sense of personal value...
Due to domain shift, deep learning image classifiers perform poorly when applied to a domain different from the training one. For instance, a classi...
Systematic literature reviews are the highest quality of evidence in research. However, the review process is hindered by significant resource and d...
Large language models (LLMs) are now being considered and even deployed for applications that support high-stakes decision-making, such as recruitme...
Nuclear magnetic resonance (NMR) crystallography is one of the main methods in structural biology for analyzing protein stereochemistry and structure....
The treatment of primary central nervous system tumors is challenging due to the blood-brain barrier and complex mutational profiles, which is associa...
Foundation models have had a big impact in recent years and billions of dollars are being invested in them in the current AI boom. The more popular ...
During the drug discovery and design process, the acid-base dissociation constant (pKa) of a molecule is critically emphasized due to its crucial role...
The American Association of Colleges of Nursing (AACN) is shifting the nursing education paradigm to competency-based education. Competency-based nurs...