Neuro-net model for early arterial hypertension diagnostics using 24-hour blood pressure monitoring data

Abstract

Aim. To improve diagnostics of arterial hypertension (AH) at early stages. Material and methods. In 34 relatively healthy individuals and 72 AH patients, 24-hour blood pressure monitoring (BPM) was performed. In all hypertensive patients, no target organ damage was registered, office BP levels were below 159/94 mm Hg. Results. Using the program imitating artificial neuronal nets, a model was developed that correctly diagnosed early AH stages, by 24-hour BPM data, in people without evident BP increase. Conclusion. Non-linear multiple modeling substantially improved early AH diagnostics in people without evident BP increase at rest.

Keywords

• артериальное давление
• артериальная гипертония
• ранняя диагностика
• моделирование