Intention-use gaps and displacement of valued activities predict social media regret more strongly than duration, with pre-session context generalizing across users and physiological signals adding person-specific predictive power.
Toward machine emotional intelligence: analysis of affective physiological state,
3 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 3representative citing papers
A unified inference-time augmentation framework with 13 methods and Bayesian-optimized parameters improves AUROC up to 8.5% and reduces false positives in PPG-based AF detection across five datasets.
Transfer learning from an arachnophobia dataset yields 86% accuracy classifying PTSD status and 17% MAPE estimating severity via HR/GSR signals and MKDE in a 21-person military cohort.
citing papers explorer
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A Comprehensive Inference-Time Augmentation Framework in Physiological Signals: Application to PPG-Based AF Detection
A unified inference-time augmentation framework with 13 methods and Bayesian-optimized parameters improves AUROC up to 8.5% and reduces false positives in PPG-based AF detection across five datasets.
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Quantitative Evaluation of the Severity of Posttraumatic Stress Disorder through Transfer Learning from Specific Phobia Data
Transfer learning from an arachnophobia dataset yields 86% accuracy classifying PTSD status and 17% MAPE estimating severity via HR/GSR signals and MKDE in a 21-person military cohort.