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Prediction of Perforated and Nonperforated Acute Appendicitis Using Machine Learning-Based Explainable Artificial Intelligence

Background: The primary aim of this study was to create a machine learning (ML) model that can predict perforated and nonperforated acute appendicitis (AAp) with high accuracy and to demonstrate the clinical interpretability of the model with explainable artificial intelligence (XAI). Method: A tota...

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Detalles Bibliográficos
Autores principales: Akbulut, Sami, Yagin, Fatma Hilal, Cicek, Ipek Balikci, Koc, Cemalettin, Colak, Cemil, Yilmaz, Sezai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10047288/
https://www.ncbi.nlm.nih.gov/pubmed/36980481
http://dx.doi.org/10.3390/diagnostics13061173