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Published 2025 | Version 1.0
Preprint Open

An Explainable Hybrid Deep Learning Approach for Histopathological Cancer Diagnosis

Authors/Creators

  • Chowdhury, Shaharior Islam (Researcher)1 ORCID icon
  • 1. ROR icon Bangladesh University of Business and Technology

Files

Files (2.8 MB)

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An Explainable Hybrid Deep Learning Approach for Histopathological Cancer Diagnosis (2).docx
md5:c6fb89c3349b139c9edf89bddc89269d
2.8 MB Download

Additional details

Software

Programming language
Python
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15
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39 39
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External resources

Indexed in
  • OpenAIRE

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Keywords and subjects

Keywords

  • cancer detection
  • Histopathological Image Analysis
  • Hybrid Deep Learning
  • DenseNet121
  • Swin Transformer
  • Cross-Attention Fusion
  • Medical Image Classification

Details

DOI
10.5281/zenodo.17401494
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DOI

10.5281/zenodo.17401494

Markdown

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.17401494.svg)](https://doi.org/10.5281/zenodo.17401494)

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Target URL

https://doi.org/10.5281/zenodo.17401494
Resource type
Preprint
Publisher
Zenodo
Languages
English

Rights

License
Copyright (C) 2025 Chowdhury, Shaharior Islam. All Rights Reserved.
This preprint is the original, author-produced version of the manuscript titled "An Explainable Hybrid Deep Learning Approach for Histopathological Cancer Diagnosis". It has not undergone peer review or editorial revision. The author(s) hold full copyright to this work and reserve all rights. Redistribution or reuse of this material in any form, electronic or print, is prohibited without the author’s written permission. Citation and academic referencing of this work are permitted. This version is made available for scholarly communication and early access to research findings. A peer-reviewed version will be submitted to an academic journal.
Copyright
Copyright (C) 2025 Chowdhury, Shaharior Islam. All Rights Reserved.

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Technical metadata

Created
October 20, 2025
Modified
October 20, 2025

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