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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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Principais autores: Benedikt Holm, Gabriel Jouan, Emil Hardarson, Sigríður Sigurðardottir, Kenan Hoelke, Conor Murphy, Erna Sif Arnardóttir, María Óskarsdóttir, Anna Sigríður Islind
Formato: Artigo
Idioma:Inglês
Publicado em: Frontiers Media S.A. 2024-05-01
coleção:Frontiers in Neuroinformatics
Assuntos:
sleep research
platform
human-in-the-loop
machine learning
scoring time
agreement
Acesso em linha:https://www.frontiersin.org/articles/10.3389/fninf.2024.1379932/full
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