<p>The uncontrolled cell proliferation in the lung region is termed lung cancer, which causes a severe mortality rate globally. Cynomys optimization. But they ended with certain difficulties such as inaccurate classification, computational complexities, interpretability issues, limited training samples, and generalizability issues. These aforementioned disadvantages are significantly tackled by a new model named improved Cynomys optimization-based transfer learning-enabled deep convolutional neural network (ICyO-TLDCN), which provides robust detection results with better performance precision. Furthermore, the model’s effectiveness and stability are strengthened by the incorporation of the ICyO algorithm, which is highly composed of nature-inspired behaviour and a transfer learning approach that, in turn, provides successive extraction of complex features and effective hyperparameter tuning. From this context, the ICyO-TLDCN improves the convergence rate along with training efficiency over optimal detection. During validation, the ICyO-TLDCN model achieves better performance under the LIDC-IDRI dataset, which attains 99.13% accuracy, 99.98% sensitivity, and 98.28% specificity.</p>