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

Lawrence Baizer; Regina Bures; Girish Nadkarni; Carolyn Reyes-Guzman; Sweta Ladwa; Brian Cade; Michael Brandon Westover; Jeffrey Durmer; Massimiliano De Zambotti; Manisha Desai; Ankit Parekh; Bing Si; Julio Fernandez-Mendoza; Kelton Minor; Diego R. Mazzotti; Soomi Lee; Dina Katabi; Orsolya Kiss; Adam P. Spira; Jonna Morris; Azizi Seixas; Marianthi Anna Kioumourtzoglou; John F.P. Bridges; Marishka Brown; Lauren Hale; Shaun Purcell

doi:10.1093/sleep/zsaf035

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

Lawrence Baizer
, Regina Bures
, Girish Nadkarni
, Carolyn Reyes-Guzman
, Sweta Ladwa
, Brian Cade
, Michael Brandon Westover
, Jeffrey Durmer
, Massimiliano De Zambotti
, Manisha Desai
, Ankit Parekh
, Bing Si
, Julio Fernandez-Mendoza
, Kelton Minor
, Diego R. Mazzotti
, Soomi Lee
, Dina Katabi
, Orsolya Kiss
, Adam P. Spira
, Jonna Morris

Azizi Seixas, Marianthi Anna Kioumourtzoglou, John F.P. Bridges, Marishka Brown, Lauren Hale, Shaun Purcell

Research output: Contribution to journal › Article › peer-review

4 Scopus citations

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.

Original language	English (US)
Article number	zsaf035
Journal	Sleep
Volume	48
Issue number	6
DOIs	https://doi.org/10.1093/sleep/zsaf035
State	Published - Jun 1 2025

All Science Journal Classification (ASJC) codes

Neuropsychology and Physiological Psychology
Clinical Psychology
Clinical Neurology
Physiology (medical)
Behavioral Neuroscience

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10.1093/sleep/zsaf035

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Baizer, L., Bures, R., Nadkarni, G., Reyes-Guzman, C., Ladwa, S., Cade, B., Westover, M. B., Durmer, J., De Zambotti, M., Desai, M., Parekh, A., Si, B., Fernandez-Mendoza, J., Minor, K., Mazzotti, D. R., Lee, S., Katabi, D., Kiss, O., Spira, A. P., ... Purcell, S. (2025). Big data approaches for novel mechanistic insights on sleep and circadian rhythms: A workshop summary. Sleep, 48(6), Article zsaf035. https://doi.org/10.1093/sleep/zsaf035

@article{1664f7e216614d3d8cfb5614c06d0f28,

title = "Big data approaches for novel mechanistic insights on sleep and circadian rhythms: A workshop summary",

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.",

author = "Lawrence Baizer and Regina Bures and Girish Nadkarni and Carolyn Reyes-Guzman and Sweta Ladwa and Brian Cade and Westover, \{Michael Brandon\} and Jeffrey Durmer and \{De Zambotti\}, Massimiliano and Manisha Desai and Ankit Parekh and Bing Si and Julio Fernandez-Mendoza and Kelton Minor and Mazzotti, \{Diego R.\} and Soomi Lee and Dina Katabi and Orsolya Kiss and Spira, \{Adam P.\} and Jonna Morris and Azizi Seixas and Kioumourtzoglou, \{Marianthi Anna\} and Bridges, \{John F.P.\} and Marishka Brown and Lauren Hale and Shaun Purcell",

note = "Publisher Copyright: {\textcopyright} 2025 Published by Oxford University Press on behalf of Sleep Research Society (SRS).",

year = "2025",

month = jun,

day = "1",

doi = "10.1093/sleep/zsaf035",

language = "English (US)",

volume = "48",

journal = "Sleep",

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Baizer, L, Bures, R, Nadkarni, G, Reyes-Guzman, C, Ladwa, S, Cade, B, Westover, MB, Durmer, J, De Zambotti, M, Desai, M, Parekh, A, Si, B, Fernandez-Mendoza, J, Minor, K, Mazzotti, DR, Lee, S, Katabi, D, Kiss, O, Spira, AP, Morris, J, Seixas, A, Kioumourtzoglou, MA, Bridges, JFP, Brown, M, Hale, L & Purcell, S 2025, 'Big data approaches for novel mechanistic insights on sleep and circadian rhythms: A workshop summary', Sleep, vol. 48, no. 6, zsaf035. https://doi.org/10.1093/sleep/zsaf035

TY - JOUR

T1 - Big data approaches for novel mechanistic insights on sleep and circadian rhythms

T2 - A workshop summary

AU - Baizer, Lawrence

AU - Bures, Regina

AU - Nadkarni, Girish

AU - Reyes-Guzman, Carolyn

AU - Ladwa, Sweta

AU - Cade, Brian

AU - Westover, Michael Brandon

AU - Durmer, Jeffrey

AU - De Zambotti, Massimiliano

AU - Desai, Manisha

AU - Parekh, Ankit

AU - Si, Bing

AU - Fernandez-Mendoza, Julio

AU - Minor, Kelton

AU - Mazzotti, Diego R.

AU - Lee, Soomi

AU - Katabi, Dina

AU - Kiss, Orsolya

AU - Spira, Adam P.

AU - Morris, Jonna

AU - Seixas, Azizi

AU - Kioumourtzoglou, Marianthi Anna

AU - Bridges, John F.P.

AU - Brown, Marishka

AU - Hale, Lauren

AU - Purcell, Shaun

PY - 2025/6/1

Y1 - 2025/6/1

N2 - 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.

AB - 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.

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UR - https://www.scopus.com/pages/publications/105008128813#tab=citedBy

U2 - 10.1093/sleep/zsaf035

DO - 10.1093/sleep/zsaf035

M3 - Article

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AN - SCOPUS:105008128813

SN - 0161-8105

VL - 48

JO - Sleep

JF - Sleep

IS - 6

M1 - zsaf035

ER -

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

Abstract

All Science Journal Classification (ASJC) codes

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