The emerging paradigm in pediatric rheumatology: harnessing the power of artificial intelligence.

Koker O., Sahin S., YILDIZ M., Adrovic A., KASAPÇOPUR Ö.

Rheumatology international, vol.44, no.11, pp.2315-2325, 2024 (SCI-Expanded, Scopus) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 44 Issue: 11
  • Publication Date: 2024
  • Doi Number: 10.1007/s00296-024-05661-x
  • Journal Name: Rheumatology international
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, BIOSIS, CAB Abstracts, Veterinary Science Database
  • Page Numbers: pp.2315-2325
  • Keywords: Artificial intelligence, Computer Vision systems, Convolutional neural network, Deep learning, Machine learning, Pediatric rheumatology
  • Marmara University Affiliated: Yes

Abstract

Artificial intelligence algorithms, with roots extending into the past but experiencing a resurgence and evolution in recent years due to their superiority over traditional methods and contributions to human capabilities, have begun to make their presence felt in the field of pediatric rheumatology. In the ever-evolving realm of pediatric rheumatology, there have been incremental advancements supported by artificial intelligence in understanding and stratifying diseases, developing biomarkers, refining visual analyses, and facilitating individualized treatment approaches. However, like in many other domains, these strides have yet to gain clinical applicability and validation, and ethical issues remain unresolved. Furthermore, mastering different and novel terminologies appears challenging for clinicians. This review aims to provide a comprehensive overview of the current literature, categorizing algorithms and their applications, thus offering a fresh perspective on the nascent relationship between pediatric rheumatology and artificial intelligence, highlighting both its advancements and constraints.