Interpretable and intervenable ultrasonography-based machine learning models for pediatric appendicitis

Appendicitis is among the most frequent reasons for pediatric abdominal surgeries. Previous decision support systems for appendicitis have focused on clinical, laboratory, scoring, and computed tomography data and have ignored abdominal ultrasound, despite its noninvasive nature and widespread avail...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	Medical image analysis 2024-01, Vol.91, p.103042-103042, Article 103042
Hauptverfasser:	Marcinkevičs, Ričards, Reis Wolfertstetter, Patricia, Klimiene, Ugne, Chin-Cheong, Kieran, Paschke, Alyssia, Zerres, Julia, Denzinger, Markus, Niederberger, David, Wellmann, Sven, Ozkan, Ece, Knorr, Christian, Vogt, Julia E
Format:	Artikel
Sprache:	eng
Schlagworte:	Appendicitis - diagnostic imaging Child Humans Machine Learning Neural Networks, Computer Tomography, X-Ray Computed Ultrasonography - methods
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!