Harvard Electroencephalography Database: A comprehensive clinical electroencephalographic resource from four Boston hospitals
Epilepsia2025Vol. 66(9), pp. 3411–3425
Citations Over TimeTop 10% of 2025 papers
Chenxi Sun, Jin Jing, Niels Turley, Callison Alcott, Wonmo Kang, Andrew J. Cole, Daniel M. Goldenholz, Alice Lam, Edilberto Amorim, Catherine J. Chu, Sydney S. Cash, Valdery Moura, Aditya Gupta, Manohar Ghanta, Bruce D. Nearing, Fábio A. Nascimento, Aaron F. Struck, Jennifer Kim, Shadi Sartipi, Alexandra‐Maria Tauton, Marta Fernandes, Haoqi Sun, Grace Bayas, Kaileigh Gallagher, Joost Wagenaar, Nishant Sinha, Christopher Lee‐Messer, Christine Tsien Silvers, Bharath Gunapati, Jonathan Rosand, Jurriaan M. Peters, Tobias Loddenkemper, Jong Woo Lee, Sahar F. Zafar, M. Brandon Westover
Abstract
HEEDB fills a critical gap in EEG data availability for epilepsy research. By enabling large-scale, privacy-compliant, and clinically relevant analysis, it accelerates the development of diagnostic tools, improves training datasets for machine learning, and promotes data-sharing in alignment with FAIR (Findable, Accessible, Interoperable, Reusable) and National Institutes of Health data policies.
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