Proceedings of the International Conference on Materials, Energy, Environment & Manufacturing Sciences & Computational Intelligence and Smart Communication (MEEMS-CISC-2024)

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Deep Learning Model for Detecting Lung Cancer from Histopathological Images

Authors
H. N. Ananya1, N. A. Anoksha1, C. V. Aravinda1, *, Apeksha Rao1, Deeksha Achar1
1Department of Computer Science and Engineering, NMAM Institute of Technology, Nitte (Deemed to Be University), Karkala, India
*Corresponding author. Email: aravinda.cv@nitte.edu.in
Corresponding Author
C. V. Aravinda
Available Online 16 June 2025.
DOI
10.2991/978-94-6463-762-5_7How to use a DOI?
Keywords
Deep Learning; CNN; TensorFlow; ResNet50; Image Classification; Lung Disease Detection
Abstract

This study introduces an AI-powered system using a customized ResNet50 model to enhance lung disease diagnostics through image analysis. Our model accurately classifies lung conditions, including adenocarcinoma, squamous cell carcinoma, and benign tissue, achieving 93.25% accuracy compared to the standard model's 74.47%. Integrating this AI solution into diagnostic workflows can significantly benefit healthcare professionals by enabling accurate and efficient detection of lung abnormalities. This can lead to improved patient outcomes and support groundbreaking medical research, ultimately transforming lung disease diagnostics and making a meaningful impact on human health.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Materials, Energy, Environment & Manufacturing Sciences & Computational Intelligence and Smart Communication (MEEMS-CISC-2024)
Series
Advances in Engineering Research
Publication Date
16 June 2025
ISBN
978-94-6463-762-5
ISSN
2352-5401
DOI
10.2991/978-94-6463-762-5_7How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - H. N. Ananya
AU  - N. A. Anoksha
AU  - C. V. Aravinda
AU  - Apeksha Rao
AU  - Deeksha Achar
PY  - 2025
DA  - 2025/06/16
TI  - Deep Learning Model for Detecting Lung Cancer from Histopathological Images
BT  - Proceedings of the International Conference on Materials, Energy, Environment & Manufacturing Sciences & Computational Intelligence and Smart Communication (MEEMS-CISC-2024)
PB  - Atlantis Press
SP  - 64
EP  - 72
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-762-5_7
DO  - 10.2991/978-94-6463-762-5_7
ID  - Ananya2025
ER  -