EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 78 (2025) ITM Web Conf., 78 (2025) 02007 References
Open Access
Issue
ITM Web Conf.
Volume 78, 2025
International Conference on Computer Science and Electronic Information Technology (CSEIT 2025)
Article Number 02007
Number of page(s) 10
Section Machine Learning Applications in Vision, Security, and Healthcare
DOI https://doi.org/10.1051/itmconf/20257802007
Published online 08 September 2025
  1. Sung, H., Ferlay, J., Siegel, R.L., Laversanne, M., Soerjomataram, I., Jemal, A., Bray, F.: 'Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries', CA: Cancer J. Clin., 2021, 71, (3), pp. 209–249 [Google Scholar]
  2. American Cancer Society: 'Cancer Facts & Figures. 2021', https://www.cancer.org/research/cancer-facts-statistics/all-cancer-facts-figures/cancer-facts-figures-2021.html, accessed 3 September 2021 [Google Scholar]
  3. Smak Gregoor, A.M., Sangers, T.E., Bakker, L.J., et al.: 'An artificial intelligence based app for skin cancer detection evaluated in a population based setting', NPJ Digit. Med., 2023, 6, (1), pp. 90 [Google Scholar]
  4. Esteva, A., Kuprel, B., Novoa, R.A., et al.: 'Dermatologist-level classification of skin cancer with deep neural networks', Nature, 2017, 542, (7639), pp. 115–118 [CrossRef] [PubMed] [Google Scholar]
  5. Disci, R., Gurcan, F., Soylu, A.: 'Advanced Brain Tumor Classification in MR Images Using Transfer Learning and Pre-Trained Deep CNN Models', Cancers, 2025, 17, (1), pp. 121 [Google Scholar]
  6. Kaddes, M., Ayid, Y.M., Elshewey, A.M., Fouad, Y.: 'Breast cancer classification based on hybrid CNN with LSTM model', Sci. Rep., 2025, 15, (1), pp. 4409 [Google Scholar]
  7. Khamsa, D., Pascal, L., Zakaria, B., et al.: 'Skin Cancer Diagnosis and Detection Using Deep Learning', IEEE Int. Conf. Electr. Eng. Adv. Technol. (ICEEAT), 2023, 1, pp. 1–6 [Google Scholar]
  8. Malo, D.C., Rahman, M.M., Mahbub, J., Khan, M.M.: 'Skin cancer detection using convolutional neural network', IEEE Annu. Comput. Commun. Workshop Conf. (CCWC), 2022, pp. 0169–0176 [Google Scholar]
  9. Gouda, W., Sama, N.U., Al-Waakid, G., et al.: 'Detection of skin cancer based on skin lesion images using deep learning', Healthcare, 2022, 10, (7), pp. 1183 [Google Scholar]
  10. Tschandl, P., Rosendahl, C., Kittler, H.: 'The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions', Sci. Data, 2018, 5, (1), pp. 1–9 [Google Scholar]
  11. Shi, Z., Zhang, F., Zhang, X., et al.: 'Application of TransUnet Deep Learning Model for Automatic Segmentation of Cervical Cancer in Small-Field T2WI Images', J. Imaging Inform. Med., 2025, Mar 4, pp. 1–6 [Google Scholar]
  12. Azizi, S., Mustafa, B., Ryan, F., et al.: 'Big self-supervised models advance medical image classification', Proc. IEEE/CVF Int. Conf. Comput. Vis., 2021, pp. 3478–3488 [Google Scholar]
  13. Chen, J., Wang, Y., Zeb, A., et al.: 'Multimodal mixing convolutional neural network and transformer for Alzheimer’s disease recognition', Expert Syst. Appl., 2025, 259, pp. 125321 [Google Scholar]
  14. Reis, H.C., Turk, V., Khoshelham, K., Kaya, S.: 'InSiNet: a deep convolutional approach to skin cancer detection and segmentation', Med. Biol. Eng. Comput., 2022, Mar 1, pp. 1–20 [Google Scholar]
  15. Hasan, M.K., Elahi, M.T., Alam, M.A., et al.: 'DermoExpert: Skin lesion classification using a hybrid convolutional neural network through segmentation, transfer learning, and augmentation', Inform. Med. Unlocked, 2022, 28, pp. 100819 [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.