Detection of Tongue-Based Myeloid Sarcoma Using Novel Cat Swarm Optimization and Comparison with Particle Swarm Optimization Algorithm

the exact scope of this research work is to compare novel cat swarm optimisation to particle swarm optimisation for tongue-based Myeloid Sarcoma detection. To perform the detection of tumor and leukemia, ten sample tongue datasets were subjected to novel Cat Swarm Optimisation and Particle Swarm Optimisation (PSO) methods, and the fiducial interval remaining at 95%. According to the simulation's performance metrics, Novel Cat Swarm Optimisation outperforms PSO (79%) in terms of accuracy, with a significant level of p = 0.001 (p0.05) in SPSS statistical analysis. From this study, the accuracy of detection of tumor and leukemia using Novel Cat Swarm Optimization showed better results than the PSO algorithm for the considered sample images.