A New Approach for Gastrointestinal Tract Findings Detection and Classification: Deep Learning-Based Hybrid Stacking Ensemble Models

A New Approach for Gastrointestinal Tract Findings Detection and Classification: Deep Learning-Based Hybrid Stacking Ensemble Models

Endoscopic procedures for diagnosing gastrointestinal tract findings depend on specialist experience and inter-observer variability. This variability can cause minor lesions to be missed and prevent early diagnosis. In this study, deep learning-based hybrid stacking ensemble modeling has been propos...

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Bibliographic Details
Main Authors: Esra Sivari, Erkan Bostanci, Mehmet Serdar Guzel, Koray Acici, Tunc Asuroglu, Tulin Ercelebi Ayyildiz
Format: Article
Language:English
Published: MDPI AG 2023-02-01
Series:Diagnostics
Subjects:
deep learning
stacking ensemble learning
gastrointestinal tract classification
endoscopy images
McNemar’s test
Online Access:https://www.mdpi.com/2075-4418/13/4/720

Internet

https://www.mdpi.com/2075-4418/13/4/720

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