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This paper is in the following e-collection/theme issue:

Perinatal Depression; Postpartum Depression; PPD (164) Pediatrics (394) Machine Learning (3382) Sleep Monitoring, Sleep Quality, Sleep Disorders (366) Sleep Medicine (57)

Published on in Vol 9 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/78937, first published .
Mother holding newborn baby in her arms near a window

Predicting Infant Sleep Patterns From Postpartum Maternal Mental Health Measures: Machine Learning Approach

Predicting Infant Sleep Patterns From Postpartum Maternal Mental Health Measures: Machine Learning Approach

Authors of this article:

Rawan AlSaad1 Author Orcid Image ;   Raghad Burjaq2 Author Orcid Image ;   Majid AlAbdulla3, 4 Author Orcid Image ;   Alaa Abd-alrazaq1 Author Orcid Image ;   Javaid Sheikh1 Author Orcid Image ;   Rajat Thomas1 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics

Journals

  1. Keshinro O, Musa A, Abayomi A, Masisi B, Zungeru A. Deep Learning for Postpartum Depression Prediction Using Behavioral Data: A Systematic Review. IEEE Access 2026;14:86560 View
  2. AlSaad R, Lin G, Albasha S, Kashani S, Thomas R. Women’s Health Wearables: From Continuous Signals to Actionable Digital Phenotypes Across the Reproductive Lifespan. Bioengineering 2026;13(8):897 View
  3. Chung S, Chu S, Jen W, Tsai C, Chen M, Lee Y, Hung C. Parental Anxiety, Depression, and Sleep Quality in Relation to Infant Sleep: A Two-Cohort Longitudinal Study. Behavioral Sleep Medicine 2026:1 View