Genetic Algorithm-Driven Hyperparameter Optimization of Capsule Networks for Predictive Analysis of Genetic Mutations

In this study the Genetic Algorithm-Driven Hyperparameter Optimization of Capsule Networks (GA-Capsule) and two prominent algorithms, Genetic Algorithms (GAs) and Capsule Networks (CapsNets), converge to revolutionize drug interaction analysis. Employing a comprehensive dataset tailored to the predictive analysis of genetic mutations, this research aims to enhance the accuracy and efficiency of identifying drug interactions—an imperative facet of healthcare. Notably, the study unearths both known and previously concealed drug interactions, underscoring its potential to bolster patient safety and optimize treatment regimens. Key findings from the research, as highlighted in the main results, include significant improvements in predictive accuracy and a substantial reduction in adverse effects. This innovative approach promises safer and more effective drug therapies, with far-reaching implications for healthcare outcomes.