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

Reviews on Innovation in Rehabilitation and Assistive Technologies (72) Pediatrics (304) Machine Learning (2261) New Diagnostic Tools and Instruments for Pediatrics (53) Applications of AI (358)

Published on in Vol 12 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/69457, first published .
Advances in Infant Cry Paralinguistic Classification—Methods, Implementation, and Applications: Systematic Review

Advances in Infant Cry Paralinguistic Classification—Methods, Implementation, and Applications: Systematic Review

Advances in Infant Cry Paralinguistic Classification—Methods, Implementation, and Applications: Systematic Review

Authors of this article:

Geofrey Owino1 Author Orcid Image ;   Bernard Shibwabo1 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics

Journals

  1. Shayegh S, Tadj C. Balanced Neonatal Cry Classification: Integrating Preterm and Full-Term Data for RDS Screening. Information 2025;16(11):1008 View
  2. McCofie A, Goldgof D, Hausmann J, Mouton P, Sun Y, Hossain M. A Review of Deep Learning Model Approach for Pain Assessment in Infant Cry Sounds. Machine Learning and Knowledge Extraction 2026;8(3):76 View
  3. Vaishnavi V, Vijayarajan S, Appathurai A, Narayanaperumal M. CRY-NET: Penta classification of infant cry signal via deep learning based dual attention ResNeSt network. Biomedical Signal Processing and Control 2026;120:110086 View