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iEDeaL: A Deep Learning Framework for Detecting Highly Imbalanced Interictal Epileptiform Discharges

Summary: Introduces iEDeaL: a compact SC neural architecture operating on raw EEG time series plus SaSu, a loss that directly optimizes Fβ to handle extreme class imbalance in interictal epileptiform discharge (IED) detection. Shows improved accuracy and efficiency on two real-world imbalanced IED datasets versus spectrogram- and DL-based baselines. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13305
Venue
VLDB
Year
2023
Pagerank
4.3690661e-05
Overall Rank
9,247 | 35.68%
DOI
10.14778/3570690.3570698

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