An End-to-End Concatenated CNN Attention Model for the Classification of Lung Cancer With XAI Techniques

An End-to-End Concatenated CNN Attention Model for the Classification of Lung Cancer With XAI Techniques

<p dir="ltr">In the field of medical imaging, deep learning (DL) techniques have made significant contributions to the detection and classification of various cancers. Identifying the precise regions in medical images containing cancerous cells plays a crucial role in the diagnostic...

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Bibliographic Details
Main Author: Fariha Haque (21485518) (author)
Other Authors: Mohammad Asif Hasan (22303759) (author), Md. Abu Ismail Siddique (22503755) (author), Tonmoy Roy (21485527) (author), Tonmoy Kanti Shaha (22503758) (author), Yamina Islam (22303756) (author), Avijit Paul (22303753) (author), Muhammad E. H. Chowdhury (14150526) (author)
Published: 2025
Subjects:
Biomedical and clinical sciences
Oncology and carcinogenesis
Health sciences
Health services and systems
Information and computing sciences
Artificial intelligence
Lung cancer
convolutional neural network
CLAHE
explainable AI
Shapley additive explanation
gradient-weighted class activation mapping
Gradio
Accuracy
Computed tomography
Feature extraction
Tumors
Transfer learning
Medical diagnostic imaging
Convolutional neural networks
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