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Workload

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Using an AI-Powered Solution to Transform Nursing Workflow and Improve Inpatient Care: A Retrospective Observational Study.

The American journal of nursing
BACKGROUND: Nurses face an escalating workload, including tasks not directly related to patient care, such as responding to patients' requests for water or extra blankets, and adjusting room conditions like air conditioning, which can contribute to b...

Utilizing Large language models to select literature for meta-analysis shows workload reduction while maintaining a similar recall level as manual curation.

BMC medical research methodology
BACKGROUND: Large language models (LLMs) like ChatGPT showed great potential in aiding medical research. A heavy workload in filtering records is needed during the research process of evidence-based medicine, especially meta-analysis. However, few st...

[Relationship between certain uses of artificial intelligence and psychosocial risk factors in European work environments].

Archivos de prevencion de riesgos laborales
INTRODUCTION: To examine the relationship between the use of Artificial Intelligence (AI) to assess and monitor job performance and exposure to psychosocial risk factors, as well as associated adverse health effects in the European work environment.

Performance metrics outperform physiological indicators in robotic teleoperation workload assessment.

Scientific reports
Robotics holds the potential to streamline the execution of repetitive and dangerous tasks, which are difficult or impossible for a human operator. However, in complex scenarios, such as nuclear waste management or disaster response, full automation ...

Development and Validation of a Literature Screening Tool: Few-Shot Learning Approach in Systematic Reviews.

Journal of medical Internet research
BACKGROUND: Systematic reviews (SRs) are considered the highest level of evidence, but their rigorous literature screening process can be time-consuming and resource-intensive. This is particularly challenging given the rapid pace of medical advancem...

Histological proven AI performance in the UKLS CT lung cancer screening study: Potential for workload reduction.

European journal of cancer (Oxford, England : 1990)
PURPOSE: Artificial intelligence (AI) could reduce lung cancer screening computer tomography (CT)-reading workload if used as a first-reader, ruling-out negative CT-scans at baseline. Evidence is lacking to support AI performance when compared to gol...

Reducing the workload of medical diagnosis through artificial intelligence: A narrative review.

Medicine
Artificial intelligence (AI) has revolutionized medical diagnostics by enhancing efficiency, improving accuracy, and reducing variability. By alleviating the workload of medical staff, AI addresses challenges such as increasing diagnostic demands, wo...

Enhanced EEG-based cognitive workload detection using RADWT and machine learning.

Neuroscience
Understanding cognitive workload improves learning performance and provides insights into human cognitive processes. Estimating cognitive workload finds practical applications in adaptive learning systems, brain-computer interfaces, and cognitive mon...

Recurrent and convolutional neural networks in classification of EEG signal for guided imagery and mental workload detection.

Scientific reports
The Guided Imagery technique is reported to be used by therapists all over the world in order to increase the comfort of patients suffering from a variety of disorders from mental to oncology ones and proved to be successful in numerous of ways. Poss...

AdaptEEG: A Deep Subdomain Adaptation Network With Class Confusion Loss for Cross-Subject Mental Workload Classification.

IEEE journal of biomedical and health informatics
EEG signals exhibit non-stationary characteristics, particularly across different subjects, which presents significant challenges in the precise classification of mental workload levels when applying a trained model to new subjects. Domain adaptation...