An optimized framework for processing multicentric polysomnographic data incorporating expert human oversight

IntroductionPolysomnographic recordings are essential for diagnosing many sleep disorders, yet their detailed analysis presents considerable challenges. With the rise of machine learning methodologies, researchers have created various algorithms to automatically score and extract clinically relevant...

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Библиографические подробности

Главные авторы:	Benedikt Holm, Gabriel Jouan, Emil Hardarson, Sigríður Sigurðardottir, Kenan Hoelke, Conor Murphy, Erna Sif Arnardóttir, María Óskarsdóttir, Anna Sigríður Islind
Формат:	Artigo
Язык:	Inglês
Опубликовано:	Frontiers Media S.A. 2024-05-01
Серии:	Frontiers in Neuroinformatics
Предметы:	sleep research platform human-in-the-loop machine learning scoring time agreement
Online-ссылка:	https://www.frontiersin.org/articles/10.3389/fninf.2024.1379932/full
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