Výsledky vyhledávání - "Sarnyai Zoltán"

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Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights

Autor: Vos, Gideon, van Eijk, Liza, Sarnyai, Zoltan, Azghadi, Mostafa Rahimi

Machine Learning is transforming medical research by improving diagnostic accuracy and personalizing treatments. General ML models trained on large datasets identify broad patterns across populations, but their effectiveness is often limited by the d

Externí odkaz: http://arxiv.org/abs/2412.16199

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The Effect of Acute Stress on the Interpretability and Generalization of Schizophrenia Predictive Machine Learning Models

Autor: Vos, Gideon, Ebrahimpour, Maryam, van Eijk, Liza, Sarnyai, Zoltan, Azghadi, Mostafa Rahimi

Introduction Schizophrenia is a severe mental disorder, and early diagnosis is key to improving outcomes. Its complexity makes predicting onset and progression challenging. EEG has emerged as a valuable tool for studying schizophrenia, with machine l

Externí odkaz: http://arxiv.org/abs/2410.19739

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Stress Monitoring Using Low-Cost Electroencephalogram Devices: A Systematic Literature Review

Autor: Vos, Gideon, Ebrahimpour, Maryam, van Eijk, Liza, Sarnyai, Zoltan, Azghadi, Mostafa Rahimi

Introduction. Low-cost health monitoring devices are increasingly being used for mental health related studies including stress. While cortisol response magnitude remains the gold standard indicator for stress assessment, a growing number of studies

Externí odkaz: http://arxiv.org/abs/2403.05577

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Ensemble Machine Learning Model Trained on a New Synthesized Dataset Generalizes Well for Stress Prediction Using Wearable Devices

Autor: Vos, Gideon, Trinh, Kelly, Sarnyai, Zoltan, Azghadi, Mostafa Rahimi

Introduction. We investigate the generalization ability of models built on datasets containing a small number of subjects, recorded in single study protocols. Next, we propose and evaluate methods combining these datasets into a single, large dataset

Externí odkaz: http://arxiv.org/abs/2209.15146

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Generalizable machine learning for stress monitoring from wearable devices: A systematic literature review

Autor: Vos, Gideon, Trinh, Kelly, Sarnyai, Zoltan, Azghadi, Mostafa Rahimi

Publikováno v: International Journal of Medical Informatics Volume 173, May 2023, 105026

Introduction. The stress response has both subjective, psychological and objectively measurable, biological components. Both of them can be expressed differently from person to person, complicating the development of a generic stress measurement mode

Externí odkaz: http://arxiv.org/abs/2209.15137

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