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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التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Fariha Haque (21485518) (author)
مؤلفون آخرون:	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)
منشور في:	2025
الموضوعات:	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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An End-to-End Concatenated CNN Attention Model for the Classification of Lung Cancer With XAI Techniques

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