Latest AI and machine learning research in staffing & scheduling for healthcare professionals.
Vehicular metaverses are an emerging paradigm that merges intelligent transportation systems with virtual spaces, leveraging advanced digital twin and Artificial Intelligence (AI) technologies to seamlessly integrate vehicles, users, and digital environments. In this paradigm, vehicular AI agents are endowed with environment perception, decision-making, and action execution capabilities, enablin...
Multimodal Large Language Models (MLLMs) have been rapidly advancing, enabling cross-modal understanding and generation, and propelling artificial intelligence towards artificial general intelligence. However, existing MLLM inference systems are typically designed based on the architecture of language models, integrating image processing and language processing as a single scheduling unit. This ...
Inverse Protein Folding (IPF) is a critical subtask in the field of protein design, aiming to engineer amino acid sequences capable of folding corre...
Multimodal medical image fusion plays a crucial role in medical diagnosis by integrating complementary information from different modalities to enha...
Auto-regressive (AR) models, initially successful in language generation, have recently shown promise in visual generation tasks due to their superi...
We present MegaScale-MoE, a production system tailored for the efficient training of large-scale mixture-of-experts (MoE) models. MoE emerges as a p...
Image enhancement methods often prioritize pixel level information, overlooking the semantic features. We propose a novel, unsupervised, fuzzy-inspi...
Machine Unlearning (MU) aims to remove the information of specific training data from a trained model, ensuring compliance with privacy regulations ...
Clinical trials are vital for evaluation of safety and efficacy of new treatments. However, clinical trials are resource-intensive, time-consuming a...
This study critically distinguishes between AI Agents and Agentic AI, offering a structured conceptual taxonomy, application mapping, and challenge ...
Demand for nursing care will intensify in the coming decades based on demographics, chronic diseases, multimorbidity and other health-related issues. ...
The integration of new employees into a company is crucial for employee satisfaction and staff retention. This paper presents a chatbot designed to op...
This study highlights domain shift in dataset distributions that impact machine learning performance in clinical natural language processing, analyzin...
In recent years, air quality levels have become a global issue with the rise of harmful pollutants and their effects on climate change. Urban areas ar...
Cardiac image segmentation is an important step in many cardiac image analysis and modeling tasks such as motion tracking or simulations of cardiac ...
Pacing is a key mechanism in modern transport protocols, used to regulate packet transmission timing to minimize traffic burstiness, lower latency, ...
Compound annotation, including the unveiling of dark matter in the metabolomics study represents a pivotal undertaking within the metabolomics field, ...
: The healthcare sector is under increasing pressure due to an ageing population, rising multimorbidity, and a projected global workforce shortage of ...
Patient recruitment remains a major bottleneck in clinical trials, calling for scalable and automated solutions. We present TrialMatchAI, an AI-powe...
The accurate determination of mycotoxins in food samples is crucial to guarantee food safety and minimize their toxic effects on human and animal heal...