The application of machine learning for infant cries classification and pathological cries detection: A systematic review.

ABSTRACT: ObjectiveThis study aims to systematically review and synthesize the studies on the application of machine learning for classifying infant cry types, identifying pathological cries, and evaluating the accuracy of infant cry recognition.MethodsThis review followed the PRISMA guidelines and was registered in PROSPERO (CRD42024600969). The literature search was conducted on four data sources: PubMed, CINAHL, Embase, and IEEE Xplore. The included studies focused on machine learning-based classification of infants' needs cries or pathological cries. These were published in English between January 1, 2014 and October 31, 2024. Study quality was assessed using the QUADAS-2 tool.ResultsOf 919 studies were identified, 17 were included in the final synthesis. Machine learning can classify infant cri

SUBMITTER: Sirithepmontree S 

PROVIDER: S-EPMC12804663 | biostudies-literature | 2026 Jan-Mar

REPOSITORIES: biostudies-literature