A deep representation learning model to predict response to vagus nerve stimulation

Abstract Implantable neurotechnologies are increasingly used to reduce seizure burden in pediatric epilepsy. Vagus nerve stimulation (VNS), the most common option, is effective for only half of patients, with no means to predict outcome prior to surgery. As a result, many children undergo invasive a...

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Principais autores:	Hrishikesh Suresh, Karim Mithani, Vicki Li, Timur H. Latypov, Nebras M. Warsi, Simeon M. Wong, Lauren Erdman, Jaeyoung Kang, Jurgen Germann, Flavia Venetucci Gouveia, Sebastian C. Coleman, Alexandre Berger, Vann Chau, Shelly Weiss, Carolina Gorodetsky, Elizabeth Donner, Alexander G. Weil, Jignesh Tailor, Taylor J. Abel, Madison Remick, Emefa Akwayena, Dewi Schrader, Robert J. Bollo, Matthew D. Smyth, Diana Aum, Sean M. Lew, Shelly Wang, Toba N. Niazi, Aria Fallah, Jeffrey S. Raskin, Howard L. Weiner, Nisha Gadgil, Gregory W. Albert, Aristides Hadjinicolaou, Philippe Major, Farbod Niazi, Guillaume Theaud, Sami Obaid, Elysa Widjaja, Birgit Ertl-Wagner, Logi Vidarsson, Margot J. Taylor, Alexandre Boutet, James T. Rutka, Melissa A. LoPresti, Puneet Jain, George M. Ibrahim
פורמט:	Artigo
שפה:	Inglês
יצא לאור:	Nature Portfolio 2026-04-01
סדרה:	Nature Communications
גישה מקוונת:	https://doi.org/10.1038/s41467-026-71555-0
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