A novel network-level fused deep learning architecture with shallow neural network classifier for gastrointestinal cancer classification from wireless capsule endoscopy images

A novel network-level fused deep learning architecture with shallow neural network classifier for gastrointestinal cancer classification from wireless capsule endoscopy images

Abstract Deep learning has significantly contributed to medical imaging and computer-aided diagnosis (CAD), providing accurate disease classification and diagnosis. However, challenges such as inter- and intra-class similarities, class imbalance, and computational inefficiencies due to numerous hype...

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Bibliographic Details
Main Authors: Muhammad Attique Khan, Usama Shafiq, Ameer Hamza, Anwar M. Mirza, Jamel Baili, Dina Abdulaziz AlHammadi, Hee-Chan Cho, Byoungchol Chang
Format: Article
Language:English
Published: BMC 2025-03-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Gastrointestinal disease
Wireless capsule endoscopy
Deep learning
LSTM
Fusion
Optimization
Online Access:https://doi.org/10.1186/s12911-025-02966-0
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