From Unimodal Tools to Multimodal Systems: A Structured Narrative Review of Selected Early-Childhood Screening, Assessment, and Monitoring Applications

Abstract

Early-childhood digital screening, clinician-supervised assessment, and monitoring use smartphone images, home video, interaction audio, caregiver questionnaires, and non-contact sensors. Yet “multimodal” is sometimes applied when distinct patient-level inputs are not jointly modeled. This structured narrative review examines selected decentralized domains—neonatal jaundice, autism-related screening or assessment, and cry or sleep monitoring—in children from birth through six years. A structured targeted update through 29 July 2026 used PubMed, IEEE Xplore, version-of-record pages, citation chaining, and official guidance. Multimodality required the joint use of two or more conceptually distinct patient-level modalities for model development, inference, or decision generation. Of 22 retained empirical reports, 9 used multimodal fusion, representing four system lineages. Validation was task-specific; prospective or external evaluation was more developed in neonatal jaundice and autism-related applications, while remote-home, postmarket, or implementation evidence was concentrated in selected autism-related lineages. Limitations included matched unimodal comparisons, calibration, determinate result coverage, missing-input handling, subgroup transportability, independent replication, referral outcomes, and deployment evaluation. A non-aggregated decision-oriented matrix organizes these requirements across technical, clinical, operational, equity, caregiver, privacy, and safety dimensions. Future studies should test whether multimodal fusion improves clinically relevant decisions over matched unimodal baselines, and whether gains persist across independent settings and care pathways.