Latest AI and machine learning research in staffing & scheduling for healthcare professionals.
Industrial compressed-air systems are characterized by nonlinear and dynamically coupled behavior, where load fluctuations and discrete compressor states jointly affect energy efficiency and operational stability. However, existing methods often decouple forecasting from scheduling and lack data-quality assessment, limiting their robustness. This paper proposes an integrated "load forecasting-dyna...
BACKGROUND: The rapid digitization of healthcare has positioned transformer-based natural language processing (NLP) models as powerful tools for managing clinical textual data. However, their integration into practice raises unresolved questions regarding equity and inclusivity. OBJECTIVE: This scoping review examines how equity is addressed in transformer-based clinical NLP, with a focus on algor...
Neurodegenerative diseases are biologically heterogeneous disorders characterized by progressive neuronal dysfunction, overlapping molecular pathologi...
INTRODUCTION: Digital technologies are increasingly integrated into neurorehabilitation programs for Parkinson's Disease (PD), enabling remote deliver...
The emerging concept of "Green Radiology" aims to mitigate the environmental impact of medical imaging while maintaining high standards of patient car...
Applications in industrial and smart-infrastructure Wireless sensor networks (WSNs) in the field are increasingly expected to employ predictive intell...
PURPOSE: Intraoperative speech monitoring during awake glioma surgery is critical to detect stimulation-induced motor speech impairments such as dysar...
OBJECTIVE: Endodontic education requires structured clinical reasoning practise, but resource constraints often limit the delivery of case-based instr...
Low-dose computed tomography (LDCT) reduces radiation dose but, introduces heterogeneous noise due to different photon attenuation based on anato...
The relative retention of nitrogen (N) and phosphorus (P) in lakes and their roles in nutrient cycling remain debated. Although the United States has ...
The rapid rise in global population and industrial activity has intensified environmental challenges, particularly carbon dioxide (COâ‚‚) emissions from...
Edge-assisted cognitive radio networks require efficient scheduling mechanisms to jointly manage opportunistic spectrum access, task offloading, energ...
Concerns about facial skin health and aesthetics are increased among the male demographic, necessitating in-depth exploration of lifestyle factors on ...
Recent advances in actuation, control and learning have rapidly pushed humanoid robots from a distant vision towards near-term real-world deployment1-...
This narrative review explores advanced Artificial Intelligence (AI) tools, particularly Convolutional Neural Network (CNN), for automated fish diseas...
BACKGROUND: Demographic shifts are increasing the global demand for long-term care services, coinciding with a worldwide shortage of health care perso...
BACKGROUND: Machine learning (ML), deep learning (DL) and other predictive modelling approaches are increasingly applied to predict antiretroviral the...
INTRODUCTION: Assessment of renal tissue and renal tumor stiffness may provide complementary information for tissue characterization; however, convent...
Drug development productivity has not improved despite five decades of computational advancement, with the probability that a compound entering Phase ...
The integration of artificial intelligence (AI) into pharmaceutical care represents a paradigm shift in healthcare delivery, offering unprecedented op...