Artificial Intelligence in Pediatric Urology.
Algorithm
Artificial intelligence
Machine learning
Model
Pediatric urology
Prediction
Journal
The Urologic clinics of North America
ISSN: 1558-318X
Titre abrégé: Urol Clin North Am
Pays: United States
ID NLM: 0423221
Informations de publication
Date de publication:
Feb 2024
Feb 2024
Historique:
medline:
13
11
2023
pubmed:
10
11
2023
entrez:
9
11
2023
Statut:
ppublish
Résumé
Application of artificial intelligence (AI) is one of the hottest topics in medicine. Unlike traditional methods that rely heavily on statistical assumptions, machine learning algorithms can identify highly complex patterns from data, allowing robust predictions. There is an abundance of evidence of exponentially increasing pediatric urologic publications using AI methodology in recent years. While these studies show great promise for better understanding of disease and patient care, we should be realistic about the challenges arising from the nature of pediatric urologic conditions and practice, in order to continue to produce high-impact research.
Identifiants
pubmed: 37945105
pii: S0094-0143(23)00075-7
doi: 10.1016/j.ucl.2023.08.002
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
91-103Informations de copyright
Copyright © 2023 Elsevier Inc. All rights reserved.