Predicting the Optimal Treatment for Diseases Using Whale Optimization Algorithm

Recently, there has been a significant research focus on addressing disease prevalence, especially in dealing with the complexities of big data associated with disease data. The challenge is achieving high accuracy due to missing value problems in big data. This study aims to use AI techniques to develop a system that predicates the optimal solutions for disease, regardless of the type of disease, i.e. the system can be applied to any type of disease. The approach involves handling missing values and normalizing disease datasets. The Whale Optimization Algorithm (WOA) will be used to improve predictions for effective disease treatments. We obtained good results for predicting the appropriate treatment for the disease in the proposed research, compared to the results obtained when applying the PSO algorithm before development in state of earlier, where the results obtained in the proposed research had higher accuracy than the results in in state of earlier at high iterations starting from 200 iterations and also had a lower error rate.: