TY  - JOUR
AU  - Kerth, Janna-Lina
AU  - Hagemeister, Maurus
AU  - Bischops, Anne C.
AU  - Reinhart, Lisa
AU  - Dukart, Juergen
AU  - Heinrichs, Bert
AU  - Eickhoff, Simon B.
AU  - Meissner, Thomas
TI  - Artificial intelligence in the care of children and adolescents with chronic diseases: a systematic review
JO  - European journal of pediatrics
VL  - 184
IS  - 1
SN  - 0340-6199
CY  - Dordrecht
PB  - Springer Science & Business Media B.V.
M1  - FZJ-2024-07208
SP  - 83
PY  - 2025
AB  - 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.
LB  - PUB:(DE-HGF)16
C6  - 39672974
UR  - <Go to ISI:>//WOS:001379523700001
DO  - DOI:10.1007/s00431-024-05846-3
UR  - https://juser.fz-juelich.de/record/1034442
ER  -