Journal Article FZJ-2024-07208

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Artificial intelligence in the care of children and adolescents with chronic diseases: a systematic review

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2025
Springer Science & Business Media B.V. Dordrecht

European journal of pediatrics 184(1), 83 () [10.1007/s00431-024-05846-3]

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Abstract: The integration of artificial intelligence (AI) and machine learning (ML) has shown potential for various applications in the medical field, particularly for diagnosing and managing chronic diseases among children and adolescents. This systematic review aims to comprehensively analyze and synthesize research on the use of AI for monitoring, guiding, and assisting pediatric patients with chronic diseases. Five major electronic databases were searched (Medline, Scopus, PsycINFO, ACM, Web of Science), along with manual searches of gray literature, personal archives, and reference lists of relevant papers. All original studies as well as conference abstracts and proceedings, focusing on AI applications for pediatric chronic disease care were included. Thirty-one studies met the inclusion criteria. We extracted AI method used, study design, population, intervention, and main results. Two researchers independently extracted data and resolved discrepancies through discussion. AI applications are diverse, encompassing, e.g., disease classification, outcome prediction, or decision support. AI generally performed well, though most models were tested on retrospective data. AI-based tools have shown promise in mental health analysis, e.g., by using speech sampling or social media data to predict therapy outcomes for various chronic conditions.

Classification:

Contributing Institute(s):
  1. Gehirn & Verhalten (INM-7)
Research Program(s):
  1. 5254 - Neuroscientific Data Analytics and AI (POF4-525) (POF4-525)

Database coverage:
Medline ; Creative Commons Attribution CC BY 4.0 ; OpenAccess ; BIOSIS Previews ; Biological Abstracts ; Clarivate Analytics Master Journal List ; Current Contents - Clinical Medicine ; Current Contents - Life Sciences ; DEAL Springer ; Ebsco Academic Search ; Essential Science Indicators ; IF < 5 ; JCR ; NationallizenzNationallizenz ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection
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Dokumenttypen > Aufsätze > Zeitschriftenaufsätze
Institutssammlungen > INM > INM-7
Workflowsammlungen > Öffentliche Einträge
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Open Access

 Datensatz erzeugt am 2024-12-17, letzte Änderung am 2025-02-03


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