K-means competitive swarm optimizer: performance benchmarking and application in brain tumor detection

Key Points

• K-means swarm optimization improves brain tumor detection accuracy by 20%, showing significant promise in early identification.
• The primary metric utilized was the detection accuracy of tumors across various datasets, ensuring robust validation.
• Assessment using performance benchmarking evaluated the algorithm's effectiveness against traditional methods and other optimization techniques.
• These findings underscore the potential for advanced algorithms to enhance early brain tumor detection, suggesting a need for further exploration in clinical settings.