Interobserver variability between experienced and inexperienced observers in the histopathological analysis of Wilms tumors: a pilot study for future algorithmic approach

Interobserver variability between experienced and inexperienced observers in the histopathological analysis of Wilms tumors: a pilot study for future algorithmic approach

Abstract Background Histopathological classification of Wilms tumors determines treatment regimen. Machine learning has been shown to contribute to histopathological classification in various malignancies but requires large numbers of manually annotated images and thus specific pathological knowledg...

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Bibliographic Details
Main Authors: Jikke J. Rutgers, Tessa Bánki, Ananda van der Kamp, Tomas J. Waterlander, Marijn A. Scheijde-Vermeulen, Marry M. van den Heuvel-Eibrink, Jeroen A. W. M. van der Laak, Marta Fiocco, Annelies M. C. Mavinkurve-Groothuis, Ronald R. de Krijger
Format: Article
Language:English
Published: BMC 2021-08-01
Series:Diagnostic Pathology
Subjects:
Wilms tumor
Interobserver variability
Machine learning
Histopathology
Classification
AI (artificial intelligence)
Online Access:https://doi.org/10.1186/s13000-021-01136-w

Internet

https://doi.org/10.1186/s13000-021-01136-w

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