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Published in Artificial Intelligence in Medicine (AIME), 2024
Natural language processing of social media to identify breast cancer medication use and reported side effects.
Recommended citation: Seibi Kobara, **Masoud Nateghi**, et al. (2024). "Social Media as a Sensor: Analyzing Twitter Data for Breast Cancer Medication Effects Using Natural Language Processing." Artificial Intelligence in Medicine (AIME).
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Published in Sensors, 2024
Kalman filter-based EEG instantaneous frequency features for automatic sleep stage classification.
Recommended citation: **Masoud Nateghi** et al. (2024). "Model-Based Electroencephalogram Instantaneous Frequency Tracking: Application in Automated Sleep-Wake Stage Classification." Sensors.
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Published in Journal of Affective Disorders, 2025
EEG event-related potential features for assessing depression and symptom severity.
Recommended citation: Bradly T. Stone, **Masoud Nateghi**, et al. (2025). "Decoding Depression: Event Related Potential Dynamics and Predictive Neural Signatures of Depression Severity." Journal of Affective Disorders.
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Published in Physiological Measurement, 2025
ECG and PPG biomarkers for depression risk prescreening.
Recommended citation: Sajjad Karimi, **Masoud Nateghi**, et al. (2025). "Prescreening Depression Using Wearable Electrocardiogram and Photoplethysmogram Data from a Psycholinguistic Experiment." Physiological Measurement.
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Published in protocols.io, 2025
A protocol for collecting multimodal physiological data in a psycholinguistic study.
Recommended citation: Reza Sameni, **Masoud Nateghi**, et al. (2025). "A Psycholinguistics Protocol with Simultaneous Multimodal Physiological Data Collection for Individualized Pre-Screening Depressive Disorders." protocols.io.
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Published in AMIA Annual Symposium, 2026
An estimation-theoretic approach to reducing bias in oscillometric blood pressure measurements.
Recommended citation: **Masoud Nateghi** et al. (2025). "Estimation-Theoretic Bias Reduction for Oscillometric Blood Pressure Readings." AMIA 2026 Annual Symposium.
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Published in IEEE Transactions on Biomedical Engineering, 2026
A Kalman filter framework for tracking directional maternal-fetal heart rate coupling.
Recommended citation: **Masoud Nateghi** et al. (2026). "A Kalman Filter-Based Framework for Granger Causality Assessment: Application in Tracking Maternal-Fetal Heart Rate Coupling." IEEE Transactions on Biomedical Engineering.
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Published in Computing in Cardiology, 2026
Self-supervised fetal heart rate representations for identifying fetal acidosis.
Recommended citation: Johann Vargas-Calixto, **Masoud Nateghi**, et al. (2026). "Self-Supervised Representation Learning of Fetal Heart Rate Outperforms a Foundation Model in Identifying Fetal Acidosis." Computing in Cardiology.
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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