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title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð±Ð°ÐºÐ°Ð»Ð°Ð²ÑÐ°
titleType: Subtitle
title: Development of a system for recognizing pathological processes in the patients heart and the risk of their occurrence in a healthy person using an electrocardiogram
Creators: name: ÐÑÐ±ÐµÐµÐ²Ð°, ÐÐ½Ð½Ð°
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2023
Subjects: Ð­ÐÐ
Ð¸ÑÐºÑÑÑÑÐ²ÐµÐ½Ð½ÑÐµ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
Ð¿Ð°ÑÐ¾Ð»Ð¾Ð³Ð¸Ð¸ ÑÐµÑÐ´ÑÐ°
Ð¾ÑÐµÐ½ÐºÐ° ÑÐ¸ÑÐºÐ° ÑÐ°Ð·Ð²Ð¸ÑÐ¸Ñ Ð¿Ð°ÑÐ¾Ð»Ð¾Ð³Ð¸Ð¹ ÑÐµÑÐ´ÑÐ°
Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ðµ Ð¾Ð±ÑÐµÐºÑÐ¾Ð²
Ð´ÐµÑÐµÐºÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ ÐºÐ»ÑÑÐµÐ²ÑÑ ÑÐ¾ÑÐµÐº Ð½Ð° Ð­ÐÐ
ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ñ Ð¿Ð°ÑÐ¾Ð»Ð¾Ð³Ð¸Ð¹
ECG
artificial neural networks
heart pathologies
risk assessment of heart pathologies
object detection
detection of key points on the ECG
classification of pathologies

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description: On the topic of the final qualifying work: "Development of a system for recognizing pathological processes in the patients heart and the risk of their occurrence in a healthy person using an electrocardiogram." The final qualifying work is devoted to the creation of a recognition system using machine learning methods. The subject of the study of this work was the automatic diagnosis of heart diseases and assessment of the risk of their occurrence in a healthy person. The object of the study of this work was the method of obtaining digitized signals from an electrocardiogram for the possibility of diagnosis. The aim of the work is to develop a system for recognizing pathological processes in the heart and the risk of their occurrence in a healthy person using an electrocardiogram. In this paper, an overview was made of the main theses of electrocardiography, the algorithm for studying the state of the heart, as well as methods for detecting objects on small data sets and methods for classifying pathologies. A system consisting of 4 software modules has been designed, and the most suitable INS models and libraries for its implementation have been selected. As a result of the final qualifying work, a recognition system based on two models of artificial neural networks was developed and tested, which is capable of classifying 8 heartbeat anomalies and 1 normal sinus rhythm, as well as assessing the risk of heart pathologies in a healthy person.