AIMC Topic: Workload
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Machine learning evaluation model of pilot workload in a low-visibility environment.
Scientific reports
Jul 1, 2025
To analyze the variation trend of pilots' workload in a low-visibility flight environment and then put forward a scientific evaluation method, this study set up an experimental platform using an E01-pro simulated flight platform and a PhysioPlux mult...
A machine learning model using clinical notes to identify physician fatigue.
Nature communications
Jul 1, 2025
Clinical notes should capture important information from a physician-patient encounter, but they may also contain signals indicative of physician fatigue. Using data from 129,228 emergency department (ED) visits, we train a model to identify notes wr...
Oxygen Uptake Prediction for Timely Construction Worker Fatigue Monitoring Through Wearable Sensing Data Fusion.
Sensors (Basel, Switzerland)
May 20, 2025
The physical workload evaluation of construction activities will help to prevent excess physical fatigue or overexertion. The workload determination involves measuring physiological responses such as oxygen uptake (VO) while performing the work. The ...
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
Apr 28, 2025
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...
Workload of diagnostic radiologists in the foreseeable future based on recent (2024) scientific advances: Updated growth expectations.
European journal of radiology
Apr 7, 2025
PURPOSE: To assess the expected impact of the 2024 medical imaging literature on the workload of diagnostic radiologists.
Recurrent and convolutional neural networks in classification of EEG signal for guided imagery and mental workload detection.
Scientific reports
Mar 27, 2025
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...
Using Optimal Feature Selection and Continuous Learning to Implement Efficient Model Arrays for Predicting Daily Clinical Radiology Workload.
Academic radiology
Mar 25, 2025
RATIONALE AND OBJECTIVE: Clinical workload can fluctuate daily in radiology practice. We sought to design, validate, and implement an efficient and sustainable machine learning model to forecast daily clinical image interpretation workload.
AdaptEEG: A Deep Subdomain Adaptation Network With Class Confusion Loss for Cross-Subject Mental Workload Classification.
IEEE journal of biomedical and health informatics
Mar 6, 2025
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)
Feb 25, 2025
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
Feb 7, 2025
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...
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