Work Force

Cross-sectional research: Application of an Artificial Intelligence-Based Pediatric Early Warning Score in the Pediatric Emergency Department.

BACKGROUND: There are a large number of pediatric emergency patients. Due to the fact that the children cannot describe their own conditions, there is a shortage of nursing staff, it is extremely important to identify the early warning signs of the children's conditions as early as possible. The current targeted care needs to be improved. OBJECTIVE: This study aimed to investigate the application ...

Public Perceptions of AI in Medicine and Implications for Future Medical Education: Cross-Sectional Survey.

BACKGROUND: The integration of artificial intelligence (AI) into clinical practice is contingent on public trust. This trust often depends on physician oversight, yet a significant gap exists between the need for AI-competent physicians and the current state of medical education. While the perspectives of students and experts on this gap are known, the views of the US general public remain largely...

Personalized Digital Care Program Allocation for Older Adults: Reinforcement Learning-Based Simulation Study.

BACKGROUND: As the demand for innovative older adult care grows alongside a shortage of care workers, personalization is key to optimizing services an...

[Expert consensus on optimizing the multidisciplinary clinical pathways and management models for pulmonary function testing].

The promotion and application of pulmonary function tests (PFTs) in China have achieved preliminary success;however, numerous deficiencies persist in ...

Generative deep learning-driven de novo design of targeted MAP4K6 inhibitors.

The discovery of selective small-molecule inhibitors for pharmacologically underexplored kinases remains a critical barrier to precision drug developm...

Bacterial taxa associated with lung cancer cases in Southeast Asians: a pilot case-control study.

PURPOSE: Lung cancer is the leading cause of cancer-related mortality worldwide, yet its underlying mechanisms remain unclear. Disruptions in the resp...

Paging the Algorithm: Applying the Best Available Human Principle to Graduate Medical Education.

Artificial intelligence (AI) is transforming graduate medical education (GME), yet formal training in its responsible use remains limited. As AI capab...

The physician as a catalyst: Reimagining medical education for an AI era.

Current medical education is caught in a paradox: it aims to train compassionate patient advocates yet its structure often fosters compliance and burn...

Predicting Radiology Burnout via Machine Learning: A Cohort Study.

RATIONALE AND OBJECTIVES: Burnout is prevalent among radiology staff, negatively impacting job satisfaction and patient care quality. This study aims ...

Application of Telehealth and Artificial Intelligence in Military Health Care: A Promising Combination for the Future.

BACKGROUND: Military and peace-support operations increasingly depend on medical capability delivered under difficult circumstances: distance, limited...

Machine-learning classification of motor unit types in the adult mouse.

Motor unit diversity arises from differences in the contractile properties of muscle fibres and the intrinsic electrical properties of their motoneuro...

Time Savings Through an AI Speech Assistant for Nursing Documentation: Pre-Post Time-Motion Study in German Long-Term Care.

BACKGROUND: Nurses in long-term care spend up to one-third of their working time on documentation, contributing to administrative burden and limited t...

aims-PAX: Parallel Active Exploration Enables Expedited Construction of Machine Learning Force Fields for Molecules and Materials.

Recent advances in machinelearning force fields (MLFFs) have significantly extended the reach of atomistic simulations. Continuous progress in this fi...

Extracellular Spike Waveforms: Morphology, Biophysics, and Classification Strategies.

Extracellular spike waveforms provide critical insights into neuronal activity, morphology, and function. Their shape can reveal cell-type identity, e...

Prediction of on-field rugby scrummaging contact forces from videos using artificial neural networks.

Rugby is a contact sport with a high risk of injury. Scrums are a key component of the game and represent a collision event associated with serious in...

Assessment of Telemedicine Perceptions, Usability, and Implementation Barriers Among Physicians in Kazakhstan Using the Telehealth Usability Questionnaire-Model for Assessment of Telemedicine-Kazakhstan Version (TUQ-MAST-KZ) Questionnaire: Pilot Cross-Sectional Survey Study.

BACKGROUND: Health care professionals' perceptions of telemedicine, its usability, and the presence of organizational barriers are important determina...

The Role of Large Language Models in Teaching Psychiatric Semiology: A Systematic Review.

INTRODUCTION: Teaching psychiatric semiology faces challenges such as the limited availability of real patients for educational purposes and a shortag...

Building Purpose-Driven Radiology Departments: Distributive and Servant Leadership in Action.

Radiology is increasingly defined by interdependence: imaging value is created through tightly coupled relationships among radiologists, technologists...

Genome diagnostics: a pillar of twenty-first century healthcare and precision medicine.

Genomic diagnostics is revolutionizing disease management and forms the cornerstone of precision medicine. This review details the multi-stage operati...

Screening and dynamic change study of microbial and metabolite markers for calf diarrhea based on multi-omics and machine learning.

UNLABELLED: Neonatal calf diarrhea is a leading cause of calf mortality and substantial economic loss in the livestock industry, yet the dynamic micro...