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All issues Volume 328 (2025) EPJ Web Conf., 328 (2025) 01045 References
Open Access
Issue
EPJ Web Conf.
Volume 328, 2025
First International Conference on Engineering and Technology for a Sustainable Future (ICETSF-2025)
Article Number 01045
Number of page(s) 17
DOI https://doi.org/10.1051/epjconf/202532801045
Published online 18 June 2025
  1. M. Wang and X. Gong, Metastatic Cancer Image Binary Classification Based on Resnet Model, IEEE 20th International Conference on Communication Technology (ICCT), China, IEEE, (2020), DOI:10.1109/ICCT50939.2020.9295797 [Google Scholar]
  2. A. Tufail, Y. Ma, K. Kaabar, F. Martinez, A. Junejo, I. Ullah, R. Khan, Deep Learning in Cancer Diagnosis and Prognosis Prediction: A Minireview on Challenges, Recent Trends, and Future Directions, (2021), Wiley Online Library. https://doi.org/10.1155/2021/9025470 [Google Scholar]
  3. K.R. Kasture, B.B. Sayankar and P.N. Matte, Multi-class Classification of Ovarian Cancer from Histopathological Images using Deep Learning-VGG-16, 2021 2nd Global Conference for Advancement in Technology (GCAT), Bangalore, India, IEEE. (2021). DOI: 10.1109/GCAT52182.2021.9587760 [Google Scholar]
  4. J. Aditya, Optimized Ensemble Prediction Model for Breast Cancer, 2021 In ternational Conference on Intelligent Technology, System and Service for Internet of Everything (ITSS-IoE), Sana'a, Yemen, IEEE, (2021). [Google Scholar]
  5. S.A. Alanazi, M.M. Kamruzzaman, Md N.I.Sarker, M. Alruwaili, Y. Alhwaiti, N. Alshammari, H. Siddiqi, Boosting Breast Cancer Detection Using Convolutional Neural Network, Wiley Online Library, (2021), DOI: 10.1155/2021/5528622 [Google Scholar]
  6. S. Kayikci and T. Khoshgoftaar, A Stack Based Multimodal Machine Learning Model for Breast Cancer Diagnosis, 2022 International Congress on Human Computer Interaction, Optimization and Robotic Applications (HORA), Ankara, Turkey, IEEE, (2022), DOI: 10.1109/HORA55278.2022.9800004 [Google Scholar]
  7. T.M. Ghazal, N. Taleb, Feature optimization and identification of ovarian cancer using internet of medical things, Wiley Online Library (2022) https://doi.org/10.1111/exsy. 12987 [Google Scholar]
  8. D. Schwartz, T.W. Sawyer, N. Thurston, J. Barton, G. Ditzler, Ovarian cancer detection using optical coherence tomography and con volutional neural networks, Springer Link (2022), DOI: 10.1007/s00521-022-06920-3 [Google Scholar]
  9. V. Saravanan, V. Sankaradass, M. Shanmathi, J.P. Bhimavarapu, M. Deivakani, S. Ramasamy, An Early Detection of Ovarian Cancer and Accurate Spreading Range in Human Body by using Deep Medical Learning Mode, 2023 International Conference on Disruptive Technologies (ICDT), Greater Noida, India, IEEE (2023), DOI: 10.1109/ICDT57929.2023.10151103 [Google Scholar]
  10. C.V. Kwatra, H. Kaur, Enhancing Ovarian Cancer Detection: A Deep Learning Approach with MobileNetV3 and ResNet50, 2023 Seventh International Conference on Image Information Processing (ICIIP), Solan, India, IEEE (2023), DOI: 10.1109/ICIIP61524.2023.10537729 [Google Scholar]
  11. S. Joshi, N. Agrawal, V. Asudani, A. Gokhale, P. Chaudhari, Cancer Detection With Machine Learning Approach: How Effective, How Progressive, 2023 IEEE 11th Region 10 Humanitarian Technology Conference (R10-HTC), Rajkot, India, IEEE(2023), DOI: 10.1109/R10-HTC57504.2023.10461904 [Google Scholar]
  12. P. Shourie, V. Anand, S. Gupta, Colon and Lung Cancer Classification of Histopathological Images Using Efficientnetb 7, 2023 3rd Asian Conference on Innovation in Technology (ASIANCON), Ravet IN, India, IEEE (2023), DOI: 10.1109/ASIANCON58793.2023.10269856 [Google Scholar]
  13. P. Bansal, V. Piuri, V. Palade, W. Ding, Deep learning in multimodal medical imaging for cancer detection, Springer Link (2023), https://doi.org/10.1007/s00521-023-08955-6 [Google Scholar]
  14. A. Boyanapalli, A. Shanthini, Ovarian cancer detection in computed tomog raphy images using ensembled deep optimized learning classifier, Wiley Online Library (2023), https://doi.org/10.1002/cpe.7716 [Google Scholar]
  15. E. Warner, J. Lee, W. Hsu, T.S. Mahmood, C.E. Kahn Jr., O. Gevaert, A. Rao, Multimodal Machine Learning in Image-Based and Clinical Biomedicine: Survey and Prospects, Springer Link (2024), https://doi.org/10.1007/s11263-024-02032-8 [Google Scholar]
  16. M. Radhakrishnan, N. Sampathila, H. Muralikrishna, K.S. Swathi, Advancing Ovarian Cancer Diagnosis Through Deep Learning and eXplainable AI: A Multiclassification Approach, IEEE Access (Volume: 12), IEEE(2024), DOI: 10.1109/ACCESS.2024.3448219 [Google Scholar]
  17. S. Ayyoubzadeh, M. Ahmadi, A.B. Yazdipour, F.G. Bidkorpeh, M. Ahmadi, Prediction of ovarian cancer using artificial intelligence tools, Wiley Online Library (2024), https://doi.org/10.1002/hsr2.2203 [Google Scholar]
  18. K.B. Maheswari, S. Gomathi, Ovarian Cancer Detection and Diagnosis Us ing Deep Learning Structure, 2024 Ninth International Conference on Science Technology Engineering and Mathematics (ICONSTEM), Chennai, India, IEEE(2024), DOI: 10.1109/ICONSTEM60960.2024.10568690 [Google Scholar]
  19. R. Tandon, S. Agrawal, N.P. Rathore, K. Abhinava, Mishra, S.K. Jain, A systematic review on deep learning-based au tomated cancer diagnosis models, 2024. Wiley Online Library (2024), https://doi.org/10.1111/icmm. 18144 [Google Scholar]
  20. R. Islam, A. Imran, F. Rabbi, Prostate Cancer Detection from MRI Using Efficient Feature Extraction with Transfer Learning, Wiley Online Library (2024), https://doi.org/10.1155/2024/1588891 [Google Scholar]

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