Study on high-dimensional biomedical data mining method based on K-Means clustering algorithm

Key Points

• The central aim is to evaluate the effectiveness of K-Means clustering in analyzing high-dimensional biomedical data.
• Application of K-Means clustering on high-dimensional datasets
• Analysis of data organization through algorithm performance
• Comparative evaluation of clustering efficiency
• K-Means clustering demonstrates efficient organization of complex biomedical data
• High-dimensional data shows improved patterns and insights post-clustering