Evaluation of artificial intelligence systems for assisting neurologists with fast and accurate annotations of scalp electroencephalography data

Evaluation of artificial intelligence systems for assisting neurologists with fast and accurate annotations of scalp electroencephalography data

Background: Assistive automatic seizure detection can empower human annotators to shorten patient monitoring data review times. We present a proof-of-concept for a seizure detection system that is sensitive, automated, patient-specific, and tunable to maximise sensitivity while minimizing human anno...

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Bibliographic Details
Main Authors: Subhrajit Roy, Isabell Kiral, Mahtab Mirmomeni, Todd Mummert, Alan Braz, Jason Tsay, Jianbin Tang, Umar Asif, Thomas Schaffter, Mehmet Eren Ahsen, Toshiya Iwamori, Hiroki Yanagisawa, Hasan Poonawala, Piyush Madan, Yong Qin, Joseph Picone, Iyad Obeid, Bruno De Assis Marques, Stefan Maetschke, Rania Khalaf, Michal Rosen-Zvi, Gustavo Stolovitzky, Stefan Harrer
Format: Article
Language:English
Published: Elsevier 2021-04-01
Series:EBioMedicine
Subjects:
Epilepsy
Seizure detection
Artificial intelligence
Deep neural networks
EEG
Automatic labelling, Crowdsourcing challenges
Online Access:http://www.sciencedirect.com/science/article/pii/S2352396421000682

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http://www.sciencedirect.com/science/article/pii/S2352396421000682

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