Cargando…
Using Machine Learning to Predict the Diagnosis, Management and Severity of Pediatric Appendicitis
Background: Given the absence of consolidated and standardized international guidelines for managing pediatric appendicitis and the few strictly data-driven studies in this specific, we investigated the use of machine learning (ML) classifiers for predicting the diagnosis, management and severity of...
Autores principales: | Marcinkevics, Ricards, Reis Wolfertstetter, Patricia, Wellmann, Sven, Knorr, Christian, Vogt, Julia E. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8116489/ https://www.ncbi.nlm.nih.gov/pubmed/33996697 http://dx.doi.org/10.3389/fped.2021.662183 |
Ejemplares similares
-
Pediatric Severe Sepsis Prediction Using Machine Learning
por: Le, Sidney, et al.
Publicado: (2019) -
Pediatric Crohn's disease diagnosis aid via genomic analysis and machine learning
por: Zheng, Zhiwei, et al.
Publicado: (2023) -
Validating the early phototherapy prediction tool across cohorts
por: Daunhawer, Imant, et al.
Publicado: (2023) -
Editorial: Current concepts and recent advances on pediatric appendicitis
por: Suominen, Janne S., et al.
Publicado: (2023) -
Increased Incidence of Perforated Appendicitis in Children During COVID-19 Pandemic in a Bavarian Multi-Center Study
por: Schäfer, Frank-Mattias, et al.
Publicado: (2021)