AIMC Topic: Workload

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The Effect of Workload and Task Priority on Multitasking Performance and Reliance on Level 1 Explainable AI (XAI) Use.

Human factors
ObjectiveThis study investigates the effects of workload and task priority on multitasking performance and reliance on Level 1 Explainable Artificial Intelligence (XAI) systems in high-stakes decision environments.BackgroundOperators in critical sett...

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...

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...

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...

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...

Learning performance and physiological feedback-based evaluation for human-robot collaboration.

Applied ergonomics
The development of Industry 4.0 has resulted in tremendous transformations in the manufacturing sector to supplement the human workforce through collaboration with robots. This emphasis on a human-centered approach is a vital aspect in promoting resi...

Self-Supervised Learning for Near-Wild Cognitive Workload Estimation.

Journal of medical systems
Feedback on cognitive workload may reduce decision-making mistakes. Machine learning-based models can produce feedback from physiological data such as electroencephalography (EEG) and electrocardiography (ECG). Supervised machine learning requires la...

Artificial Intelligence and Radiologist Burnout.

JAMA network open
IMPORTANCE: Understanding the association of artificial intelligence (AI) with physician burnout is crucial for fostering a collaborative interactive environment between physicians and AI.

Novel multimodal sensing and machine learning strategies to classify cognitive workload in laparoscopic surgery.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
BACKGROUND: Surgeons can experience elevated cognitive workload (CWL) during surgery due to various factors including operative technicalities and the environmental demands of the operating theatre. This can result in poorer outcomes and have a detri...