Applications of Artificial Intelligence for Visual and Auditory Screening in Neonates: A Scoping Review

Introduction: Childhood hearing and visual impairment negatively affect development and impose a significant social and economic burden. Neonatal screening is essential for early detection and intervention, improving prognosis and social integration. With advances in artificial intelligence, new diagnostic tools have emerged that promise greater accuracy and broader coverage. This study aims to map the applications and impact of artificial intelligence (AI) in neonatal hearing and visual screening worldwide, identifying its benefits, limitations, and potential for future implementation. Methodology: A scoping review will be conducted to analyze scientific articles, reviews, technical literature, and grey literature published between 2015 and 2025, encompassing the available evidence on artificial intelligence modalities in neonatal hearing and visual screening globally. Databases such as PubMed, Scopus, Web of Science, and BIREME will be included, utilizing MeSH and DeCS descriptors related to artificial intelligence, hearing screening, visual screening, and neonates. This will be complemented with grey literature, and, if necessary, the snowballing technique will be employed to identify additional relevant studies. Expected Results: This study is expected to provide a comprehensive overview of the main artificial intelligence modalities contributing to neonatal hearing and visual screening worldwide, identifying AI tools and applications relevant to healthcare in this field. The findings will generate valuable evidence for healthcare professionals and service planners, facilitating the design of strategies and interventions aimed at advancing scientific knowledge in this area and opening new horizons for improvements in healthcare delivery.