Work begins with a description of the neurons as the main part of the nervous system. It is indicated that the analogy of natural neuron and artificial neuron as a node within the artificial neural network architecture is very similar. It was showned connection between processes that occur at the level of artificial intelligence algorithms and natural processes which are characteristic for people. After that, different artificial intelligence algorithms for the prediction of the appearance of the sepsis are described separately. First, it was described an SVM algorithm with corresponding program codes. The SVM algorithm was first applied to percent normalized data, and then to normalized data using a special library. After explanation of the program code, there are given results for both SVM algorithms. After that, it was performed the implementation of KNN algorithm for the given problem. An algorithm was examined with different values of coefficient k. After explanation of the corresponding code, the solutions were presented and it was given a brief overview of the efficiency for three explained models. Finally, the symbolic regression algorithm was implemented for the given problem. It was examined a large number of different regressor models (4704 models), among was selected the most optimal model based on mean squared error. Results and comments about that regressor model are given below. In the end, all the previous conclusions are compiled and it was made a decision which algorithm is most beneficial for real implementation.