ArticleJapanese journal of radiology2019
Monitoring of fatigue in radiologists during prolonged image interpretation using fNIRS.
Article in Japanese journal of radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 32 citations in OpenAlex.
- Deep learning in pulmonary nodule detection and segmentation: a systematic review.European radiology · 2025Pooled it
- Comparing Interactive Machine Learning and Unassisted Segmentation of Geographic Atrophy From Fundus Autofluorescence.Translational vision science & technology · 2026Article
- Cognitive state monitoring for neuroadaptive information visualization.Frontiers in human neuroscience · 2026Review
- Enhanced pulmonary nodule detection with U-Net, YOLOv8, and swin transformer.BMC medical imaging · 2025Article
- The state of the art in assessing mental fatigue in the cockpit using head-worn sensing technology.Frontiers in neuroergonomics · 2025Review
- Broad learning solution for rapid diagnosis of COVID-19.Biomedical signal processing and control · 2023Article
- Assessing the development of mental fatigue during simulated flights with concurrent EEG-fNIRS measurement.Scientific reports · 2023Article
- Automatic Cognitive Fatigue Detection Using Wearable fNIRS and Machine Learning.Sensors (Basel, Switzerland) · 2022Article
- Variations in breast cancer detection rates during mammogram-reading sessions: does experience have an impact?The British journal of radiology · 2022Article
- A practical artificial intelligence system to diagnose COVID-19 using computed tomography: A multinational external validation study.Pattern recognition letters · 2021Article
- Radiologist-Level Two Novel and Robust Automated Computer-Aided Prediction Models for Early Detection of COVID-19 Infection from Chest X-ray Images.Arabian journal for science and engineering · 2021Article
- Real-World fNIRS Brain Activity Measurements during Ashtanga Vinyasa Yoga.Brain sciences · 2021Article
- Application of deep learning technique to manage COVID-19 in routine clinical practice using CT images: Results of 10 convolutional neural networks.Computers in biology and medicine · 2020Article
Corrections and comments
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Authors and funding
13 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo determine whether functional near-infrared spectroscopy (fNIRS) allows monitoring fatigue in radiologists during prolonged image interpretation. MATERIALS AND
methodsNine radiologists participated as subjects in the present study and continuously interpreted medical images and generated reports for cases for more than 4 h under real clinical work conditions. We measured changes in oxygenated hemoglobin concentrations [oxy-Hb] in the prefrontal cortex using 16-channel fNIRS (OEG16ME, Spectratech) every hour during the Stroop task to evaluate fatigue of radiologists and recorded fatigue scale (FS) as a behavior data.
resultsTwo subjects showed a subjective feeling of fatigue and an apparent decrease in brain activity after 4 h, so the experiment was completed in 4 h. The remaining seven subjects continued the experiment up to 5 h. FS decreased with time, and a significant reduction was observed between before and the end of image interpretation. Seven out of nine subjects showed a minimum [oxy-Hb] change at the end of prolonged image interpretation. The mean change of [oxy-Hb] at the end of all nine subjects was significantly less than the maximum during image interpretation.
conclusionfNIRS using the change of [oxy-Hb] may be useful for monitoring fatigue in radiologists during image interpretation.
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