Speculation of lung cancer using deep learning sequential and CNN model
Ravi Raj Choudharyraviraj@curaj.ac.inDepartment of Computer ScienceCentral University of RajasthanAjmer, Rajasthan, 305817, IndiaView full profile → , Himanshu Kumar Prashar2021imscs012@curaj.ac.inDepartment of Computer ScienceCentral University of RajasthanAjmer, Rajasthan, 305817, IndiaView full profile → , *Gaurav MeenaCorresponding authorgaurav.meena@curaj.ac.inDepartment of Computer ScienceCentral University of RajasthanAjmer, Rajasthan, 305817, IndiaView full profile →
* Corresponding author · click or hover a name for details
- Received:
- 01 Apr 2025
- Published Online:
- 23 Apr 2026
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JIOS-2292
- Pages:
- 2011–2019
Abstract
Keywords
Subject Classifications
References
[1] D. Aberle, W. Hsu, A. A. T. Bui, S. Shen, and S. X. Han, “An interpretable deep hierarchical semantic convolutional neural network for lung nodule malignancy classification,” Expert Syst. Appl., vol. 128, pp. 84–95 (2018).
[2] S. Alzahrani, “Explainable lung cancer classification with ensembled transfer learning of VGG16, ResNet50 and InceptionV3 using Grad-CAM,” BMC Med. Imaging, vol. 24, art. no. 176 (2024).
[3] R. Maheshwari and V. Kapoor, “Predicting the NSE stock index trends considering global financial variables and ARIMA model,” J. Stat. Manage. Syst., vol. 25, no. 7, pp. 1513–1522 (2022).
[4] M. Bhuiyan, I. K. Chowdhury, M. Haider, and A. H. Jisan, “Advancements in early detection of lung cancer in public health: A comprehensive study utilizing machine learning algorithms and predictive models,” J. Comput. Sci. Technol. Stud., vol. 6, no. 1, pp. 113–121 (2024).
[5] F. Mercaldo, M. G. Tibaldi, L. Lombardi, L. Brunese, A. Santone, and M. Cesarelli, “An explainable method for lung cancer detection and localization from tissue images through convolutional neural networks,” Electronics, vol. 13, no. 7, p. 1393 (2024).
[6] L. J. Crasta, R. Neema, and A. R. Pais, “A novel deep learning architecture for lung cancer detection and diagnosis from computed tomography image analysis,” Healthcare Anal., vol. 5, p. 100316 (2024).
[7] A. El-Latif, P. Plawiak, M. A. ElAffendi, A. Ateya, M. Hammad, and G. Ali, “Explainable AI for lung cancer detection via a custom CNN on CT images,” Sci. Rep., vol. 15, art. no. 12707 (2025).
[8] A. Goyal, R. K. Shrivastava, M. Agarwal, and N. Joshi, “Enhanced prediction of lung cancer using machine learning,” in Proc. 7th Int. Conf. Contemp. Comput. Informatics (IC3I), vol. 7, pp. 1478–1483 (2024).
[9] N. K. Karthikeyan, S. S. Ali, and R. V. Sekhar, “Lung cancer classification using CT scan images through deep learning and CNN-based model,” in Proc. Int. Conf. Adv. Data Eng. Intell. Comput. Syst. (ADICS), pp. 1–5 (2024).
[10] C. Jacob and G. C. Menon, “Pathological categorization of lung carcinoma from multimodality images using convolutional neural networks,” Int. J. Imaging Syst. Technol., vol. 32, no. 5, pp. 1681–1695 (2022).
[11] M. Saad and T. S. Choi, “Deciphering unclassified tumors of non-small-cell lung cancer through radiomics,” Comput. Biol. Med., vol. 91, pp. 222–230 (2017).
[12] J. Liu, J. Cui, F. Liu, Y. Yuan, F. Guo, and G. Zhang, “Multi-subtype classification model for non-small cell lung cancer based on radiomics: SLS model,” Med. Phys., vol. 46, no. 7, pp. 3091–3100 (2019).
[13] P. Marentakis, P. Karaiskos, V. Kouloulias, N. L. Kelekis, S. Argentos, N. Oikonomopoulos, and C. Loukas, “Lung cancer histology classification from CT images based on radiomics and deep learning models,” Med. Biol. Eng. Comput., vol. 59, no. 1, pp. 215–226 (2021), doi:10.1007/s11517-020-02302-w




