Staffing & Scheduling

Predicting Pediatric Urological Surgery Duration Through Multimodal Patient-Physician Feature Fusion: Deep Learning Framework Incorporating Clinical Text Embedding.

BACKGROUND: Accurate prediction of surgical duration is critical for optimizing operating room scheduling and resource allocation. Existing models, however, exhibit limited applicability in pediatric urology due to the unique anatomical and developmental characteristics of children. OBJECTIVE: This study aimed to develop and validate a specialty-tailored prediction framework for estimating the dur...

Minimization of operation and energy loss costs to improve economic and operation objectives of micro-grids manger considering sustainable computing.

This paper proposes a sustainable computing-oriented framework for economic energy scheduling in renewable energy hubs equipped with stationary storage systems within coupled electrical and thermal microgrid environments. The proposed formulation aims to simultaneously reduce operational expenditures and energy loss-related costs by defining a unified optimization objective. The framework integrat...

Improving efficiency and workflows in the nonoperating room anesthesia setting.

PURPOSE OF REVIEW: Nonoperating room anesthesia (NORA) services are rapidly expanding and now represent a substantial proportion of anesthetic care. E...

Deep learning-assisted proteomic dissection reveals sex biased and shared proteomic patterns in Populus deltoides under waterlogging stress and subsequent recovery.

Sexual dimorphism in dioecious tree species and proteomic responses under stress represents an underappreciated axis of stress resilience. Here, we in...

Code Cracked: Using Artificial Intelligence to Transform Nursing Case Studies Into Virtual Escape Rooms.

BACKGROUND: Artificial intelligence (AI) is transforming nursing education by offering innovative strategies to support clinical judgment, engagement,...

DDA-BERT: end-to-end training for data-dependent acquisition mass spectrometry-based proteomics.

Peptide-spectrum match (PSM) rescoring is critical for accurate peptide identification in data-dependent acquisition (DDA)-based proteomics. Existing ...

Energy-constrained workflow scheduling for DVFS-enabled heterogeneous systems in cloud computing environments.

Generative artificial intelligence use in medical research: A medical student vs. physician survey from Saudi Arabia.

INTRODUCTION: Generative artificial intelligence (GenAI) such as ChatGPT, is increasingly used to generate research ideas, aid in literature reviews, ...

Are LLM-generated plain language summaries truly understandable? A large-scale crowdsourced evaluation.

Plain language summaries (PLSs) are essential for facilitating effective communication between clinicians and patients by making complex medical infor...

Tech That Scales: A Practical Framework for Artificial Intelligence-Enabled Cancer Care in Low- and Middle-Income Countries and Underserved US Counties.

Cancer outcomes remain starkly unequal: 5-year survival rates for common malignancies in low- and middle-income countries (LMICs) often lag 20-40 perc...

Nurses' Lived Experiences of Generative Artificial Intelligence-Enabled Shift Handover Innovation: A Descriptive Phenomenological Study.

AIM: To explore nurses' lived experiences of a generative artificial intelligence-enabled shift handover innovation. DESIGN: A descriptive phenomenolo...

Predicting Agitation Stability of Monoclonal Antibodies during Developability Assessment.

Developability assessment facilitates the selection of antibody drug candidates with desirable pharmaceutical properties. However, it remains uncertai...

Characterizing public comments via Regulations.gov in response to proposed cannabis rescheduling in the United States.

AIMS: The United States Drug Enforcement Administration's (DEA) proposed rescheduling of cannabis from Schedule I to Schedule III under the Controlled...

Hierarchical coordinated scheduling algorithm for reactive power and voltage in cross-regional power grids based on multi-agent reinforcement learning.

To address the challenges of strong dynamic coupling, action space dimension explosion, and voltage imbalance in reactive power and voltage scheduling...

Optimizing Timeliness of Healthcare Delivery in Diagnostic Radiology at U.S. Academic Centers.

RATIONALE AND OBJECTIVES: Timely radiology access is essential for accurate diagnosis, treatment planning, and efficient care delivery. U.S. academic ...

CO coadsorption effects on the water-gas shift reaction over Cu clusters on Cu(111): insights from the machine learning force field and microkinetic modeling.

CO-induced Cu clustering has been observed experimentally and theoretically, yet its catalytic implications remain insufficiently understood. Here, we...

Machine learning-driven alignment architecture of heterogeneous data with transient varying semantics.

Via cross-correlation algorithms or synchronized acquisition of signals, the alignment of heterogeneous data with unknown semantic time shifts and int...

Novel Knotted Solenoid fold with order-shifted coil arrangement leads to nontrivial 31 topology.

Herein, we present crystal structures of proteins adopting a fold not identified among known [Formula: see text]-solenoids in current structural datab...

Edge-enabled IoT framework for real-time tobacco quality monitoring.

Tobacco quality inspection plays a vital role in ensuring standardized processing, reducing economic losses, and improving industrial automation. Howe...

Mid-term power load forecasting using an ensemble deep learning model with BKA and CWGAN-GP enhancements.

Electric load forecasting serves as a crucial decision-making foundation for the operation of power systems, offering important guidance for system sc...