This article is devoted to the methodological issues of the application of artificial intelligence techniques in preventive medicine. We showed a specific example of the neural network application allows not only to diagnose cardiovascular diseases, but also on a quantitative basis to predict their emergence and development in future periods of life. This allows you to select the optimal strategy for the prevention and treatment of patients based on their individual parameters. The article concluded: recommendations for the prevention and treatment of cardiac patients should be given strictly individually, taking into account physiological peculiarities of the organism of patients. If for some patients it is useful to give up Smoking, limit the consumption of sweets, take drugs, reduce blood pressure, etc., for other patients, these recommendations may cause harm. Our intelligent system helps to identify such non-standard patients and to avoid incorrect recommendations. The prototype of the proposed system laid out in the "Projects" section on the website www.PermAi.ru.
Because of the strategy of early diagnosis of arterial hypertension (AH) the majority of patients with prescription of the antihypertensive therapy (AHT) have grade 1 hypertension (AH1). Accumulated scientific evidence on the efficacy and safety of AHT for AH1 is insufficient for introduction of the active therapy, and the balance of harms and benefits is not clear in relation to AHT for AH1. The development of the next generation Russian guidelines for AH management in application to AH1 should take into account the totality of the scientific evidence as well as the perspective of the introduction of the national drug provision scheme. The best way to do it is to introduce more accurate diagnostic criteria for AH1 and the recommendation not to initiate the drug AHT for AH1 in cases of low cardiovascular risk.