Found: 8
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Extracting relevance and affect information from physiological text annotation.
- Published in:
- User Modeling & User-Adapted Interaction, 2016, v. 26, n. 5, p. 493, doi. 10.1007/s11257-016-9184-8
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- Article
Classification of Alzheimer's Disease Leveraging Multi-task Machine Learning Analysis of Speech and Eye-Movement Data.
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- Frontiers in Human Neuroscience, 2021, v. 15, p. 1, doi. 10.3389/fnhum.2021.716670
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- Article
Machine learning analysis of speech and eye tracking data to distinguish Alzheimer's clinic patients from healthy controls: Biomarkers: Searching for Alzheimer's through the eyes.
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- Alzheimer's & Dementia: The Journal of the Alzheimer's Association, 2020, v. 16, n. 11, p. 1, doi. 10.1002/alz.046742
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- Article
Integrating neurophysiologic relevance feedback in intent modeling for information retrieval.
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- Journal of the Association for Information Science & Technology, 2019, v. 70, n. 9, p. 917, doi. 10.1002/asi.24161
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- Article
Natural brain-information interfaces: Recommending information by relevance inferred from human brain signals.
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- Scientific Reports, 2016, p. 38580, doi. 10.1038/srep38580
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- Article
Motivational intensity and visual word search: Layout matters.
- Published in:
- PLoS ONE, 2019, v. 14, n. 7, p. 1, doi. 10.1371/journal.pone.0218926
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- Article
On the Reliability of Wearable Technology: A Tutorial on Measuring Heart Rate and Heart Rate Variability in the Wild.
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- Sensors (14248220), 2023, v. 23, n. 13, p. 5863, doi. 10.3390/s23135863
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- Article
Differentiating memory clinic patients and healthy volunteers using machine‐learning analysis of speech and eye movements during a reading task.
- Published in:
- Alzheimer's & Dementia: The Journal of the Alzheimer's Association, 2021, v. 17, p. 1, doi. 10.1002/alz.055717
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- Article