Staffing & Scheduling

The future outlook for data in orthopedic surgery: A new era of real-time innovation.

The orthopedic field is on the brink of a significant transformation-a shift from retrospective analysis to real-time decision-making fueled by data. The dependence on historical trends or long-term studies is yielding to an era where data flows dynamically, allowing medical professionals to adjust protocols instantly. This isn't just an evolution; it's a revolution. Data is no longer a passive ob...

Prediction of Chromatographic Retention Time of a Small Molecule from SMILES Representation Using a Hybrid Transformer-LSTM Model.

Accurate retention time (RT) prediction in liquid chromatography remains a significant consideration in molecular analysis. In this study, we explore the use of a transformer-based language model to predict RTs by treating simplified molecular input line entry system (SMILES) sequences as textual input, an approach that has not been previously utilized in this field. Our architecture combines a pr...

Remote monitoring of Tai Chi balance training interventions in older adults using wearable sensors and machine learning.

Tai Chi, an Asian martial art, is renowned for its health benefits, particularly in promoting healthy aging among older adults, improving balance, and...

Advancements in automated nuclei segmentation for histopathology using you only look once-driven approaches: A systematic review.

Histopathology image analysis plays a pivotal role in disease diagnosis and treatment planning, relying heavily on accurate nuclei segmentation for ex...

The AI-environment paradox: Unraveling the impact of artificial intelligence (AI) adoption on pro-environmental behavior through work overload and self-efficacy in AI learning.

This study examines the complex relationships among artificial intelligence (AI) adoption in organizations, employee work overload, and pro-environmen...

Critical scenarios adversarial generation method for intelligent vehicles testing based on hierarchical reinforcement architecture.

The widespread deployment of intelligent vehicles necessitates comprehensive testing across diverse driving scenarios. A significant challenge is gene...

A longitudinal observational study with ecological momentary assessment and deep learning to predict non-prescribed opioid use, treatment retention, and medication nonadherence among persons receiving medication treatment for opioid use disorder.

BACKGROUND: Despite effective treatments for opioid use disorder (OUD), relapse and treatment drop-out diminish their efficacy, increasing the risks o...

Application effect of rehabilitation robots in rehabilitation of limb movement disorders based on neural network algorithms.

With the continuous advancement of computer technology and sensor technology, rehabilitation robots have shown great potential in the rehabilitation t...

Innovative Technologies for Smarter and Efficient Operating Room Scheduling.

An optimized scheduling system for surgical procedures is considered fundamental for maximizing hospital resource utilization and improving patient ou...

Developing a deep learning model for the automated monitoring of acupuncture needle insertion: enhancing safety in traditional acupuncture practices.

BACKGROUND: Acupuncture is a widely practiced traditional therapy, yet safety concerns, particularly needle breakage and retention, remain critical is...

Aggregation induced emission luminogen bacteria hybrid bionic robot for multimodal phototheranostics and immunotherapy.

Multimodal phototheranostics utilizing single molecules offer a "one-and-done" approach, presenting a convenient and effective strategy for cancer the...

Exploring predictors of insomnia severity in shift workers using machine learning model.

INTRODUCTION: Insomnia in shift workers has distinctive features due to circadian rhythm disruption caused by reversed or unstable sleep-wake cycle wo...

Young doctors' attrition and retention in the GP scheme: a national cohort study from Norway.

AIMS: Several countries struggle with general practitioner (GP) burnout, recruitment and retention. The reasons are not well understood. The aim of th...

Leveraging Generative Artificial Intelligence to Improve Motivation and Retrieval in Higher Education Learners.

Generative artificial intelligence (GenAI) presents novel approaches to enhance motivation, curriculum structure and development, and learning and ret...

Effect of training sample size, image resolution and epochs on filamentous and floc-forming bacteria classification using machine learning.

Computer vision techniques can expedite the detection of bacterial growth in wastewater treatment plants and alleviate some of the shortcomings associ...

FIORA: Local neighborhood-based prediction of compound mass spectra from single fragmentation events.

Non-targeted metabolomics holds great promise for advancing precision medicine and biomarker discovery. However, identifying compounds from tandem mas...

Online Unsupervised Adaptation of Latent Representation for Myoelectric Control During User-Decoder Co-Adaptation.

Myoelectric control interfaces, which map electromyographic (EMG) signals into control commands for external devices, have applications in active pros...

PROPERMAB: an integrative framework for prediction of antibody developability using machine learning.

Selection of lead therapeutic molecules is often driven predominantly by pharmacological efficacy and safety. Candidate developability, such as biophy...

Development of artificial neural network model for anaerobic digestion-elutriated phase treatment.

Nonlinear autoregressive exogenous (NARX) neural network models were used to forecast the time-series profiles of anaerobic digestion-elutriated phase...

An quality evaluation method based on three-dimensional integration and machine learning: Advanced data processing.

This study presents an innovative approach for the quality evaluation of traditional Chinese medicine (TCM) by integrating three-dimensional (3D) data...