A large amount of data is generated and stored during haemogram measurements. A lot of useful information can be found in these data sets. Statistical analysis of these values can explore new connections and patterns which were unknown until now.
In this semester the topic of my thesis was analysis of haemogram measurements. I investigated the connections between the measurement values in the whole database and in the groups of the database. I researched the main differences and interesting patterns in the correlation networks to give useful feedback to the medical science.
For my work I used correlation analysis to examine and describe the connections. I separated the database in three different ways and tested the behaviors of these clusters. I built correlation networks for the groups which helped for the visualizations and gived opportunity to research the behavior of connections from a new angle.
During my task I wrote a Python script code, which prepare the database, calculate the correlationa for the database and the part groups and finally build the correlation networks. After all I visualized and analyzed the differences between the networks.