ReviewDiscover mental health2025
A systematic bibliometric and meta analysis of key factors and emerging AI and ML insights in shaping child cognitive development.
Review in Discover mental health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The study aims to provide scholars, professionals and others with a thorough analysis of how advanced technologies, specifically Artificial Intelligence (AI) and Machine Learning (ML), can be integrated in the early diagnosis of children's cognitive development. Adopting both systematic and bibliometric approaches, the review encompasses 122 journal articles published over the last 10 years. The analysis reveals that the majority of research work for the diagnosis of cognitive development in early childhood has been done via traditional statistical methods. The application of integrating AI and ML in early cognitive diagnosis remains limited and underexplored. The study provides academics and practitioners with important insights for continuing endeavors and possible future advances by identifying the primary factors, focus, and trends in child cognitive development. This will promote a deeper understanding of approaches to diagnosing children's cognitive development. This understanding is especially relevant in low-resource settings like India, where accessible and non-stigmatizing cognitive assessment tools can empower parents to recognize developmental delays early. Integrating AI and ML-driven solutions with culturally adapted, user-friendly platforms can bridge existing gaps and support timely interventions for long-term cognitive growth.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.