A Hybrid Deep Learning and Machine Learning Approach with Mobile-EfficientNet and Grey Wolf Optimizer for Lung and Colon Cancer Histopathology Classification
The findings suggest that our approach enhances classification performance and offers improved generalizability for real-world clinical applications. The proposed MEGWO-LCCHC framework shows promise as a robust tool in cancer diagnostics, advancing the application of AI in oncology.
Authors
- Raquel Ochoa-Ornelas (ORCID: https://orcid.org/0000-0003-1824-5789)
- Julio Alberto García-Rodríguez (ORCID: https://orcid.org/0000-0003-0339-0545)
- Alberto Gudiño-Ochoa (ORCID: https://orcid.org/0000-0002-2366-7452)
Institutions
- Universidad de Guadalajara (MX)
- Tecnológico Nacional de México (MX)
- Instituto Tecnológico de Ciudad Juárez (MX)
- Instituto Tecnológico de Ciudad Guzmán
Publication Details
- Journal
- Cancers
- Published
- 2024-11-11
- DOI
- https://doi.org/10.3390/cancers16223791
- Citations
- 26
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 9.03
Funders
- Tecnológico Nacional de México