Chemometric Expertise Of Clinical Monitoring Data Of Prolactinoma Patients

Abstract

The present investigation indicates hidden relationships between the several clinical parameters usually monitored on prolactinoma patients using non-hierarchical cluster analysis. The major goal of the chemometric data mining is to offer a possible mode of optimization of the monitoring procedure by selecting a reduced number of health status indicators. The intelligent data analysis reveals the formation of three patterns of prolactinoma patients each one of them described by a set of clinical parameters. Thus, better strategies for considering patients with this diagnosis could be developed and clinically applied.

Keywords

• non-hierarchical clustering
• prolactinoma
• clinical indicators