| Popis: |
Cardiovascular diseases remain the main cause of death among adult population; their incidence can be reduced only using an effective system of primary and secondary prevention. The aim of our study was to develop software for automated recognition of cardiovascular risk factors, prognosis, and evaluation of dyslipoproteinemia phenotypes in lipid centers. Prognostic indexes, lipidogram values are estimated, and the program detects the risk factors (overweight, poor physical training, irrational nutrition, tobacco smoking, etc.) and predicts the summary risk of coronary disease. Neuronal network was used for evaluating the types of dyslipoproteinemias and for cardiovascular prognosis. The input vectors were lipid and lipoprotein concentrations. Output neurons were diagnostic signs of dislipoproteinemia phenotypes or cardiovascular prognosis. |
