Advancements in pediatric obstructive sleep apnea: cognitive implications and the role of AI in precision medicine
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View abstract on PubMed
Summary
This summary is machine-generated.Pediatric obstructive sleep apnea impacts children's cognition, with research growing rapidly. AI and machine learning offer new hope for early detection and personalized treatments to improve neurodevelopmental outcomes.
Area Of Science
- Pediatric Sleep Medicine
- Neurodevelopmental Disorders
- Bibliometrics
Background
- Pediatric obstructive sleep apnea (OSA) is linked to cognitive impairment, exacerbated by fragmented sleep, hypoxia, and ADHD.
- This can lead to poor academic performance, behavioral issues, and developmental delays in children.
- Understanding these connections is crucial for effective interventions.
Purpose Of The Study
- To analyze the bibliometric and scientometric landscape of research on pediatric obstructive sleep apnea and its cognitive implications.
- To identify key trends, influential authors, institutions, and evolving research areas.
- To map the intellectual structure and collaborative networks within this field.
Main Methods
- A comprehensive bibliometric and scientometric analysis was performed using Web of Science Core Collection and Scopus databases.
- 1,610 studies published between 1983 and 2025 were included after data cleaning.
- CiteSpace, VOSviewer, and the R-based Bibliometrix package were utilized for data analysis.
Main Results
- Research on pediatric OSA and cognition has surged since 2010, with an 11.96% annual growth rate.
- The United States, China, and European countries are leading contributors, with prominent institutions and influential researchers identified.
- Key research themes include OSA, children, sleep-disordered breathing, cognition, ADHD, obesity, and emerging AI/ML applications for early detection.
Conclusions
- The link between pediatric OSA and neurocognitive development is a growing research focus, emphasizing cognitive outcomes and new technologies.
- Conventional treatments show limited cognitive recovery, highlighting the need for early diagnosis and personalized therapies.
- AI and machine learning advancements are enhancing diagnostic accuracy and enabling precision medicine for improved neurocognitive function in children.
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