Expert-level automated sleep staging of long-term scalp electroencephalography recordings using deep learning.

Journal: Sleep
PMID:

Abstract

STUDY OBJECTIVES: Develop a high-performing, automated sleep scoring algorithm that can be applied to long-term scalp electroencephalography (EEG) recordings.

Authors

  • Maurice Abou Jaoude
    Epilepsy Division, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
  • Haoqi Sun
    Neurology Department, Massachusetts General Hospital, Wang 720, Boston, MA, USA.
  • Kyle R Pellerin
    Epilepsy Division, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
  • Milena Pavlova
    Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA.
  • Rani A Sarkis
    Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA.
  • Sydney S Cash
    Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.
  • M Brandon Westover
    Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts.
  • Alice D Lam
    Epilepsy Division, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA. Electronic address: Lam.Alice@mgh.harvard.edu.