DeepCGAN: early Alzheimer's detection with deep convolutional generative adversarial networks
The DeepCGAN significantly improves early AD detection accuracy and robustness by enhancing the dataset diversity and leveraging advanced GAN techniques, leading to better generalization and higher performance in comparison to traditional and contemporary methods. These results demonstrate the ecacy of DeepCGAN in enhancing early AD detection, thereby potentially improving patient outcomes through timely intervention.
Authors
- Khursheed Aurangzeb (ORCID: https://orcid.org/0000-0003-3647-8578)
- Musaed A. Alhussein (ORCID: https://orcid.org/0000-0002-5538-6778)
- Nasir Saleem (ORCID: https://orcid.org/0000-0003-0010-0629)
- Qazi Mazhar ul Haq (ORCID: https://orcid.org/0000-0002-1302-7689)
- Imran Ali (ORCID: https://orcid.org/0000-0001-6511-8374)
- Benazeer Zohra
Institutions
- Gomal University (PK)
- King Saud University (SA)
- University of Swat (PK)
- Noida International University (IN)
- Institute of Medical Sciences (IN)
- Sharda University (IN)
- Yuan Ze University (TW)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2024-08-29
- DOI
- https://doi.org/10.3389/fmed.2024.1443151
- Citations
- 4
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 1.39
Funders
- King Saud University