| Title: | Artificial intelligence and pediatrics : synthetic knowledge synthesis |
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| Authors: | ID Završnik, Jernej (Author)
ID Kokol, Peter (Author)
ID Žlahtič, Bojan (Author)
ID Blažun Vošner, Helena (Author) |
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| Files: |  electronics-13-00512.pdf (1,71 MB)
MD5: 11B36648B8C7C3C08D660EE337E73FA1
 https://www.mdpi.com/2079-9292/13/3/512
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| Language: | English |
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| Work type: | Article |
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| Typology: | 1.02 - Review Article |
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| Organization: | FERI - Faculty of Electrical Engineering and Computer Science
MF - Faculty of Medicine
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| Abstract: | The first publication on the use of artificial intelligence (AI) in pediatrics dates back to
1984. Since then, research on AI in pediatrics has become much more popular, and the number of
publications has largely increased. Consequently, a need for a holistic research landscape enabling
researchers and other interested parties to gain insights into the use of AI in pediatrics has arisen. To
fill this gap, a novel methodology, synthetic knowledge synthesis (SKS), was applied. Using SKS,
we identified the most prolific countries, institutions, source titles, funding agencies, and research
themes and the most frequently used AI algorithms and their applications in pediatrics. The corpus
was extracted from the Scopus (Elsevier, The Netherlands) bibliographic database and analyzed using
VOSViewer, version 1.6.20. Done An exponential growth in the literature was observed in the last
decade. The United States, China, and Canada were the most productive countries. Deep learning was
the most used machine learning algorithm and classification, and natural language processing was
the most popular AI approach. Pneumonia, epilepsy, and asthma were the most targeted pediatric
diagnoses, and prediction and clinical decision making were the most frequent applications. |
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| Keywords: | pediatrics, artificial intelligence, synthetic knowledge synthesis, bibliometrics, machine learning |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Submitted for review: | 06.01.2024 |
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| Article acceptance date: | 25.01.2024 |
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| Publication date: | 26.01.2024 |
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| Publisher: | MDPI |
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| Year of publishing: | 2024 |
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| Number of pages: | 14 str. |
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| Numbering: | Vol. 13, iss. 3, [article no.] 512 |
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| PID: | 20.500.12556/DKUM-93540  |
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| UDC: | 004.5 |
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| ISSN on article: | 2079-9292 |
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| COBISS.SI-ID: | 182783747 |
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| DOI: | 10.3390/electronics13030512 |
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| Copyright: | © 2024 by the authors |
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| Publication date in DKUM: | 01.07.2025 |
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| Views: | 205 |
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| Downloads: | 12 |
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| Metadata: |    |
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| Categories: | Misc.
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