Big data approaches for novel mechanistic insights on sleep and circadian rhythms: a workshop summary.

Journal: Sleep
Published Date:

Abstract

The National Center on Sleep Disorders Research of the National Heart, Lung, and Blood Institute at the National Institutes of Health hosted a 2-day virtual workshop titled Big Data Approaches for Novel Mechanistic Insights on Disorders of Sleep and Circadian Rhythms on May 2nd and 3rd, 2024. The goals of this workshop were to establish a comprehensive understanding of the current state of sleep and circadian rhythm disorders research to identify opportunities to advance the field by using approaches based on artificial intelligence and machine learning. The workshop showcased rapidly developing technologies for sensitive and comprehensive remote analysis of sleep and its disorders that can account for physiological, environmental, and social influences, potentially leading to novel insights on long-term health consequences of sleep disorders and disparities of these health problems in specific populations.

Authors

  • Lawrence Baizer
    National Center on Sleep Disorders Research, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA.
  • Regina Bures
    National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA.
  • Girish Nadkarni
    Division of Data-Driven and Digital Medicine (D3M), The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Carolyn Reyes-Guzman
    National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
  • Sweta Ladwa
    National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA.
  • Brian Cade
    Brigham & Women's Hospital, Boston, Massachusetts.
  • Michael Brandon Westover
    Department of Neurology, Massachusetts General Hospital, Boston, MA, United States.
  • Jeffrey Durmer
    Sleep & Circadian Science, Absolute Rest, Denver, CO, USA.
  • Massimiliano de Zambotti
    Center for Health Sciences, SRI International, Menlo Park, CA 94025, USA.
  • Manisha Desai
    Quantitative Science Unit, Department of Medicine, Stanford University School of Medicine, Stanford, Calif.
  • Ankit Parekh
  • Bing Si
    School of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ, USA.
  • Julio Fernandez-Mendoza
    Penn State College of Medicine Sleep Research and Treatment Center, Pennsylvania State University College of Medicine, Hershey, PA, USA.
  • Kelton Minor
    Copenhagen Center for Social Data Science, University of Copenhagen, Copenhagen, Denmark.
  • Diego R Mazzotti
    Division of Medical Informatics, University of Kansas Medical Center, Kansas City, KS, USA.
  • Soomi Lee
    Department of Human Development and Family Studies, Center for Healthy Aging, Pennsylvania State University, University Park, PA, USA.
  • Dina Katabi
    Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Orsolya Kiss
    Center for Health Sciences, SRI International, 333 Ravenswood Ave, Menlo Park, CA, 94025, USA. orsolya.kiss@sri.com.
  • Adam P Spira
    Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
  • Jonna Morris
    School of Nursing, University of Pittsburgh, Pittsburgh, PA, USA.
  • Azizi Seixas
    Department of Informatics and Health Data Science, University of Miami Miller School of Medicine, Coral Gables, Florida.
  • Marianthi-Anna Kioumourtzoglou
  • John F P Bridges
    Department of Biomedical Informatics, The Ohio State University College of Medicine, Columbus, OH, United States.
  • Marishka Brown
    National Center on Sleep Disorders Research, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA.
  • Lauren Hale
    Renaissance School of Medicine, Stony Brook University, Stony Brook, NY, USA.
  • Shaun Purcell
    Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.