AIMC Topic: Workload

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Machine learning evaluation model of pilot workload in a low-visibility environment.

Scientific reports
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
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...

Effects of robot arm design and movement speed during human-robot interaction.

Applied ergonomics
The purpose of this experiment was to investigate the effect of robot arm size, movement speed, and degrees of freedom on perceived safety, trust, mental workload, human behaviors, and task performance in a collaborative pick-and-place task. Fifty-si...

Simulating workload reduction with an AI-based prostate cancer detection pathway using a prediction uncertainty metric.

European radiology
OBJECTIVES: This study compared two uncertainty quantification (UQ) metrics to rule out prostate MRI scans with a high-confidence artificial intelligence (AI) prediction and investigated the resulting potential radiologist's workload reduction in a c...

Cognitive Lab: A dataset of biosignals and HCI features for cognitive process investigation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Attention, cognitive workload/fatigue, and emotional states significantly influence learning outcomes, cognitive performance, and human-machine interactions. However, existing assessment methodologies fail to fully capture t...

Oxygen Uptake Prediction for Timely Construction Worker Fatigue Monitoring Through Wearable Sensing Data Fusion.

Sensors (Basel, Switzerland)
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
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
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
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
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.