ИСТИНА

Nowadays due to the technological progress in medicine it is possible to yield a lot of unique information about each patient. This allows one to think about the personalized approach that considers not only patient’s individual clinical features but also tumor’s bio-molecular features and provides a treatment for each patient. One of the possible ways are probabilistic models on the base of Bayesian networks (BNs), since they are capable of self-learning and self-improvement as the accumulation of experimental information and are insensitive to possible erroneous or incomplete data. BNs with naive topology has been used for a prediction of progression or death in breast cancer patients on the base of different prognostic parameters including expression and tumor’s cell localization of multifunctional protein YB-1.