title: Ð£Ð¿ÑÐ°Ð²Ð»ÐµÐ½Ð¸Ðµ Ð¿Ð¾ÑÐ¾ÐºÐ°Ð¼Ð¸ Ð¿Ð°ÑÐ¸ÐµÐ½ÑÐ¾Ð² Ñ Ð¾ÑÑÑÑÐ¼ ÐºÐ¾ÑÐ¾Ð½Ð°ÑÐ½ÑÐ¼ ÑÐ¸Ð½Ð´ÑÐ¾Ð¼Ð¾Ð¼ Ð² Ð½Ð°ÑÐ¸Ð¾Ð½Ð°Ð»ÑÐ½Ð¾Ð¼ Ð¼ÐµÐ´Ð¸ÑÐ¸Ð½ÑÐºÐ¾Ð¼ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°ÑÐµÐ»ÑÑÐºÐ¾Ð¼ ÑÐµÐ½ÑÑÐµ (Ð¿Ð¾ Ð·Ð°ÐºÐ°Ð·Ñ Ð¤ÐÐÐ£ Â«ÐÐÐÐ¦ Ð¸Ð¼. Ð.Ð. ÐÐ»Ð¼Ð°Ð·Ð¾Ð²Ð°Â» ÐÐ¸Ð½Ð·Ð´ÑÐ°Ð²Ð° Ð Ð¾ÑÑÐ¸Ð¸): Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð¿ÑÐ¾Ð³Ð½Ð¾ÑÑÐ¸ÑÐµÑÐºÐ¾Ð¹ Ð¼Ð¾Ð´ÐµÐ»Ð¸ Ð½Ð°ÑÑÑÐ¿Ð»ÐµÐ½Ð¸Ñ Ð½ÐµÐ±Ð»Ð°Ð³Ð¾Ð¿ÑÐ¸ÑÑÐ½ÑÑ ÐºÐ»Ð¸Ð½Ð¸ÑÐµÑÐºÐ¸Ñ ÑÐ¾Ð±ÑÑÐ¸Ð¹ Ð² Ð¿Ð¾ÑÐ»ÐµÐ¾Ð¿ÐµÑÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð¼ Ð¿ÐµÑÐ¸Ð¾Ð´Ðµ
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Management of acute coronary syndrome patient flows in a national medical research center (commissioned by the V.A. Almazov national medical research center of the ministry of health of Russia): development of a prognostic model for the occurrence of adverse clinical events in the postoperative period
Creators: name: ÐÐµÐºÐµÑÐ°ÐµÐ², ÐÐ¼Ð¸ÑÑÐ¸Ð¹
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: 2024
Subjects: ÑÐ¿ÑÐ°Ð²Ð»ÐµÐ½Ð¸Ðµ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð´Ð°Ð½Ð½ÑÑ
Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
ÑÐ¿ÑÐ°Ð²Ð»ÐµÐ½Ð¸Ðµ Ð¿Ð¾ÑÐ¾ÐºÐ°Ð¼Ð¸ Ð¿Ð°ÑÐ¸ÐµÐ½ÑÐ¾Ð²
Ð¿ÑÐ¾ÑÐµÑÑÐ½Ð¾Ðµ ÑÐ¿ÑÐ°Ð²Ð»ÐµÐ½Ð¸Ðµ
Ð´ÐµÑÐµÐ²Ð¾ ÑÐµÑÐµÐ½Ð¸Ð¹
data-driven management
machine learning
patient flow management
process management
decision tree

description: Ð¦ÐµÐ»Ñ Ð²ÑÐ¿ÑÑÐºÐ½Ð¾Ð¹ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÑ â Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ðµ ÑÐµÑÐ½Ð¾Ð»Ð¾Ð³Ð¸Ð¹ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð´Ð»Ñ Ð¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð½Ð°ÑÑÑÐ¿Ð»ÐµÐ½Ð¸Ñ Ð½ÐµÐ±Ð»Ð°Ð³Ð¾Ð¿ÑÐ¸ÑÑÐ½ÑÑ ÐºÐ»Ð¸Ð½Ð¸ÑÐµÑÐºÐ¸Ñ Ð¸ÑÑÐ¾Ð´Ð¾Ð² Ñ Ð¿Ð°ÑÐ¸ÐµÐ½ÑÐ¾Ð² Ð² Ð¿Ð¾ÑÐ»ÐµÐ¾Ð¿ÐµÑÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð¼ Ð¿ÐµÑÐ¸Ð¾Ð´Ðµ. Ð Ð°Ð±Ð¾ÑÐ° Ð±ÑÐ»Ð° Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½Ð° Ð½Ð° Ð±Ð°Ð·Ðµ Ð¤ÐÐÐ£ Â«ÐÐÐÐ¦ Ð¸Ð¼. Ð.Ð. ÐÐ»Ð¼Ð°Ð·Ð¾Ð²Ð°Â» ÐÐµÑÐ¾Ð´Ñ: ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð¸ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ Ð¼Ð¾Ð´ÐµÐ»Ð¸ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ ÐÑÐ½Ð¾Ð²Ð½ÑÐµ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÑ, Ð¿Ð¾Ð»ÑÑÐµÐ½Ð½ÑÐµ Ð² ÑÐ¾Ð´Ðµ ÑÐ°Ð±Ð¾ÑÑ: 1) ÐÐ¿Ð¸ÑÐ°Ð½Ð° Ð¿ÑÐ¾Ð±Ð»ÐµÐ¼Ð°ÑÐ¸ÐºÐ° ÑÐ¿ÑÐ°Ð²Ð»ÐµÐ½Ð¸Ñ Ð¿Ð¾ÑÐ¾ÐºÐ°Ð¼Ð¸ Ð¿Ð°ÑÐ¸ÐµÐ½ÑÐ¾Ð² Ñ Ð¾ÑÑÑÑÐ¼ ÐºÐ¾ÑÐ¾Ð½Ð°ÑÐ½ÑÐ¼ ÑÐ¸Ð½Ð´ÑÐ¾Ð¼Ð¾Ð¼; 2) ÐÐ¿Ð¸ÑÐ°Ð½Ñ ÑÐ¾Ð²ÑÐµÐ¼ÐµÐ½Ð½ÑÐµ Ð¿Ð¾Ð´ÑÐ¾Ð´Ñ Ðº ÑÐ¿ÑÐ°Ð²Ð»ÐµÐ½Ð¸Ñ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð´Ð°Ð½Ð½ÑÑ Ð² Ð¼ÐµÐ´Ð¸ÑÐ¸Ð½ÑÐºÐ¸Ñ Ð¾ÑÐ³Ð°Ð½Ð¸Ð·Ð°ÑÐ¸ÑÑ; 3) ÐÑÐµÐ½ÐµÐ½Ð° Ð°ÐºÑÑÐ°Ð»ÑÐ½Ð¾ÑÑÑ Ð²ÐµÐ´ÐµÐ½Ð¸Ñ Ð½Ð¾Ð·Ð¾Ð»Ð¾Ð³Ð¸ÑÐµÑÐºÐ¸Ñ ÑÐµÐ³Ð¸ÑÑÑÐ¾Ð²; 4) ÐÐ¾ÑÑÑÐ¾ÐµÐ½Ð° Ð¼Ð¾Ð´ÐµÐ»Ñ Ð¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð½Ð°ÑÑÑÐ¿Ð»ÐµÐ½Ð¸Ñ Ð½ÐµÐ±Ð»Ð°Ð³Ð¾Ð¿ÑÐ¸ÑÑÐ½ÑÑ ÐºÐ»Ð¸Ð½Ð¸ÑÐµÑÐºÐ¸Ñ Ð¸ÑÑÐ¾Ð´Ð¾Ð² Ñ Ð¿Ð°ÑÐ¸ÐµÐ½ÑÐ¾Ð² Ñ Ð¾ÑÑÑÑÐ¼ ÐºÐ¾ÑÐ¾Ð½Ð°ÑÐ½ÑÐ¼ ÑÐ¸Ð½Ð´ÑÐ¾Ð¼Ð¾Ð¼ Ð² Ð¿Ð¾ÑÐ»ÐµÐ¾Ð¿ÐµÑÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð¼ Ð¿ÐµÑÐ¸Ð¾Ð´Ðµ; 5) ÐÑÐµÐ´Ð»Ð¾Ð¶ÐµÐ½Ñ Ð¸Ð·Ð¼ÐµÐ½ÐµÐ½Ð¸Ñ Ð¿Ð¾Ð´ÑÐ¾Ð´Ð¾Ð² Ðº ÑÐ±Ð¾ÑÑ Ð´Ð°Ð½Ð½ÑÑ Ð´Ð»Ñ Ð¿Ð¾Ð²ÑÑÐµÐ½Ð¸Ñ ÐºÐ°ÑÐµÑÑÐ²Ð° Ð¸Ñ Ð°Ð½Ð°Ð»Ð¸ÑÐ¸ÐºÐ¸. ÐÐ±Ð»Ð°ÑÑÑ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ñ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð² ÐÐÐ : Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ðµ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð² ÑÐ°Ð±Ð¾ÑÑ Ð² Ð¾Ð±Ð»Ð°ÑÑÐ¸ Ð¼Ð°ÑÑÑÑÑÐ¸Ð·Ð°ÑÐ¸Ð¸ Ð¿Ð°ÑÐ¸ÐµÐ½ÑÐ¾Ð² Ñ Ð¾ÑÑÑÑÐ¼ ÐºÐ¾ÑÐ¾Ð½Ð°ÑÐ½ÑÐ¼ ÑÐ¸Ð½Ð´ÑÐ¾Ð¼Ð¾Ð¼ ÐÐ°ÑÑÐ½Ð°Ñ Ð½Ð¾Ð²Ð¸Ð·Ð½Ð° ÐÐÐ  Ð·Ð°ÐºÐ»ÑÑÐ°ÐµÑÑÑ Ð² Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ð¸ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð´Ð»Ñ Ð¼Ð°ÑÑÑÑÑÐ¸Ð·Ð°ÑÐ¸Ð¸, Ð¿Ð»Ð°Ð½Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð¸ Ð¾ÑÐµÐ½ÐºÐ¸ ÑÐ¾ÑÑÐ¾ÑÐ½Ð¸Ñ Ð¿Ð°ÑÐ¸ÐµÐ½ÑÐ¾Ð² Ñ Ð¾ÑÑÑÑÐ¼ ÐºÐ¾ÑÐ¾Ð½Ð°ÑÐ½ÑÐ¼ ÑÐ¸Ð½Ð´ÑÐ¾Ð¼Ð¾Ð¼. ÐÑÐ²Ð¾Ð´Ñ: ÐÐ°Ð´Ð°ÑÐ¸ ÐÐÐ  ÑÐµÑÐµÐ½Ñ, ÑÐµÐ»Ñ Ð´Ð¾ÑÑÐ¸Ð³Ð½ÑÑÐ°, Ð¾Ð¿ÑÐµÐ´ÐµÐ»ÐµÐ½Ð° Ð¾Ð±Ð»Ð°ÑÑÑ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ñ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð².
description: The aim of the masters thesis is the application of machine learning technologies to predict the onset of adverse clinical outcomes in patients in the postoperative period. The work was carried out on the basis of FGBU âV.A. Almazov NMRCâ Methods: development and training of machine learning model. The main results obtained in the course of the work: 1) The problematics of management of patient flows with acute coronary syndrome is described; 2) Modern approaches to data-driven management in medical organizations are described; 3) The relevance of maintaining nosologic registries is assessed; 4) A model for predicting the onset of unfavorable clinical outcomes in patients with acute coronary syndrome in the postoperative period has been built; 5) Suggested changes in approaches to data collection to improve the quality of data analytics. Scope of application masters thesis results: application of the results of work in the field of routing of patients with acute coronary syndrome. Scientific novelty masters thesis consists in the application of machine learning methods for routing, planning and evaluation of patients with acute coronary syndrome. Conclusions: The objectives of the VKR have been solved, the goal has been achieved, and the scope of application of the results has been determined.