Residual-SwishNet: a deep learning-based approach for reliable lung cancer classification

Our approach has significantly outperformed existing state-of-the-art techniques. These findings highlight the potential of the proposed model as a robust and reliable tool for lung cancer diagnosis.

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Publication Details

Journal
Frontiers in Oncology
Published
2026-01-26
DOI
https://doi.org/10.3389/fonc.2025.1729021
Primary Topic
Imbalanced Data Classification Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Residual-SwishNet: a deep learning-based approach for reliable lung cancer classification

Abdul Khader Jilani Saudagar, Ali Javed, Marriam Nawaz
Frontiers in Oncology
Imbalanced Data Classification Techniques
article

Residual-SwishNet: a deep learning-based approach for reliable lung cancer classification

Abdul Khader Jilani Saudagar, Ali Javed, Marriam Nawaz
article en

Abstract

Our approach has significantly outperformed existing state-of-the-art techniques. These findings highlight the potential of the proposed model as a robust and reliable tool for lung cancer diagnosis.

Frontiers in OncologyVol. 15
University of Engineering and Technology Taxila (PK), Imam Mohammad ibn Saud Islamic University (SA), Islamic University (BD)
Al-Imam Muhammad Ibn Saud Islamic University
Good health and well-being
Openalex Percentile: Top 79%
Imbalanced Data Classification Techniques
DOIOpen Access PDFOpenAlex
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