Enhancing Multi Cancer Classification with VGG and EfficientNet
B Gowtham · International Journal for Research in Applied Science and Engineering Technology · 2025
The present study aims to develop a reliable multi-cancer classifier based on CNNs for the diagnosis of cervical, brain, kidney, lymphoma, lung, colon, oral, and breast cancers. In this research, the CNN named VGG and EfficientNet networks were used and compared to establish how well we can achieve at differentiating medical images into cancerous and non-cancerous categories. The comparisons of experimental results indicated that the proposed VGG has a better performance than EfficientNet based on various measurements including accuracy, precision, recall and F1 score. Moreover, the experimental results showed that the VGG achieved faster convergence rate and had more effective learning rate. The results imply that the VGG model is useful for multi-cancer distinguishing tasks and can be applied to accelerate the methods for cancer diagnostics in clinical practice