The medical diagnosis and determine a correct medical procedure represent a comprehensive process that consists of many input information and potential associations. This information can lead to clinical reasoning to resolve a patient's health problem and set the treatment. Effective communication between the medical expert and data analyst can support this process more effectively, dependent on the available data. It is essential to create a shared vocabulary for this cooperation to reduce possible misunderstandings and unnecessary experiments. In our work, we performed exploratory data analysis, statistical tests, correlation analysis, and logistic regression in close cooperation with the participated expert thanks to whom we could verify the achieved results of our models. The collaboration between the medical expert and data analytic requires a lot of communication and explanation from the medical expert because of the correct interpretation of the medical data and its resulting associations. On the other hand, it requires a proper understanding of the task from the data analyst's point of view, a lot of iterations of graphs, and other models, which must be modified to be easy to read and interpret.