Artificial intelligence in medicine: neural networks for analyzing systemic hemodynamics

Abstract

Artificial neural networks are capable of efficiently processing large data sets, as well as solving the tasks of prediction, classification and data recovery. The article considers each of the above tasks in detail and studies literature sources devoted to the topic under study. Artificial neural networks cope with the tasks with a high degree of accuracy. The methods of application of neural networks for the analysis of systemic haemodynamics are described. Modern neural networks can analyse medical data and are able to work with incomplete data, find hidden patterns in them, and can be adapted to solve a wide range of problems. Our laboratory is developing an artificial neural network capable of classifying indicators describing the state of haemodynamics of subjects and recovering missing or incomplete data. Thus, artificial neural networks can act as an efficient method of analysing systemic hemodynamic parameters.