title: ÐÐ½Ð°Ð»Ð¸Ð· ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð² ÐºÐ»Ð¸Ð½Ð¸ÑÐµÑÐºÐ¸Ñ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ð¹ Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ
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: Analysis of the results of clinical trials using machine learning methods
Creators: name: Ð¡Ð¼Ð¸ÑÐ½Ð¾Ð²Ð°, ÐÐ»Ð°ÑÐ°
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: Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ñ
ÐºÐ»Ð¸Ð½Ð¸ÑÐµÑÐºÐ¸Ðµ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ
ÑÐµÐ³ÑÐµÑÑÐ¸Ñ
ÑÑÐ±ÐµÑÐºÑÐ»ÑÐ·
machine learning
classification
clinical research
regression
tuberculosis

description: ÐÐ±ÑÐµÐºÑ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ: Ð½Ð°Ð±Ð¾Ñ Ð´Ð°Ð½Ð½ÑÑ, ÑÐ¾Ð±Ð¸ÑÐ°ÐµÐ¼ÑÐ¹ Ð²ÑÐ°ÑÐ°Ð¼Ð¸-ÑÑÐ¸Ð·Ð¸Ð°ÑÑÐ°Ð¼Ð¸ Ð¿ÑÐ¸ Ð¿ÐµÑÐ²Ð¸ÑÐ½Ð¾Ð¼ Ð¾ÑÐ¼Ð¾ÑÑÐµ Ð±Ð¾Ð»ÑÐ½Ð¾Ð³Ð¾, Ñ Ð¿Ð¾Ð´ÑÐ²ÐµÑÐ¶Ð´ÐµÐ½Ð½ÑÐ¼ Ð´Ð¸Ð°Ð³Ð½Ð¾Ð·Ð¾Ð¼ Â«Ð¢ÑÐ±ÐµÑÐºÑÐ»ÑÐ·Â». Ð¦ÐµÐ»ÑÑ Ð´Ð°Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÑ ÑÐ²Ð»ÑÐµÑÑÑ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð¼ÐµÐ´Ð¸ÑÐ¸Ð½ÑÐºÐ¾Ð¹ Ð¸Ð½ÑÐ¾ÑÐ¼Ð°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹ ÑÐ¸ÑÑÐµÐ¼Ñ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð² ÐºÐ»Ð¸Ð½Ð¸ÑÐµÑÐºÐ¸Ñ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ð¹ Ð¸ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ðµ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð´Ð»Ñ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð½Ð°Ð±Ð¾ÑÐ° Ð´Ð°Ð½Ð½ÑÑ. ÐÐ°Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð²ÐºÐ»ÑÑÐ°ÐµÑ ÑÑÐ¸ Ð³Ð»Ð°Ð²Ñ. Ð Ð¿ÐµÑÐ²Ð¾Ð¹ Ð³Ð»Ð°Ð²Ðµ Ð¾Ð¿Ð¸ÑÑÐ²Ð°ÐµÑÑÑ Ð¿ÑÐµÐ´Ð¼ÐµÑÐ½Ð°Ñ Ð¾Ð±Ð»Ð°ÑÑÑ Ð´Ð°Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÑ, Ð°ÐºÑÑÐ°Ð»ÑÐ½ÑÐµ Ð¿ÑÐ¾Ð±Ð»ÐµÐ¼Ñ Ð² ÑÑÐµÑÐµ Ð¸Ð½ÑÐµÐºÑÐ¸Ð¾Ð½Ð½ÑÑ Ð·Ð°Ð±Ð¾Ð»ÐµÐ²Ð°Ð½Ð¸Ð¹. Ð Ð°ÑÑÐ¼Ð¾ÑÑÐµÐ½Ñ Ð¿ÑÐ¸Ð¼ÐµÑÑ ÑÐ¾Ð³Ð¾, ÐºÐ°Ðº Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ Ð¼Ð¾Ð¶ÐµÑ ÑÐ¿Ð¾ÑÐ¾Ð±ÑÑÐ²Ð¾Ð²Ð°ÑÑ Ð°Ð²ÑÐ¾Ð¼Ð°ÑÐ¸Ð·Ð°ÑÐ¸Ð¸ Ð½ÐµÐºÐ¾ÑÐ¾ÑÑÑ Ð¿ÑÐ¾ÑÐµÑÑÐ¾Ð² Ð² Ð¼ÐµÐ´Ð¸ÑÐ¸Ð½Ðµ. ÐÐ¿Ð¸ÑÐ°Ð½Ñ Ð·Ð°Ð´Ð°ÑÐ° ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸, Ð¼ÐµÑÐ¾Ð´Ñ ÐµÐµ ÑÐµÑÐµÐ½Ð¸Ñ. ÐÐ¾ Ð²ÑÐ¾ÑÐ¾Ð¹ Ð³Ð»Ð°Ð²Ðµ Ð¾Ð¿Ð¸ÑÐ°Ð½Ñ Ð¾ÑÐ½Ð¾Ð²Ð½ÑÐµ Ð¼ÐµÑÐ¾Ð´Ñ ÑÐµÑÐµÐ½Ð¸Ñ Ð·Ð°Ð´Ð°ÑÐ¸ Ð±Ð¸Ð½Ð°ÑÐ½Ð¾Ð¹ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸, Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ñ ÑÐµÑÐµÐ½Ð¸Ñ Ð¿Ð¾ÑÑÐ°Ð²Ð»ÐµÐ½Ð½Ð¾Ð¹ Ð·Ð°Ð´Ð°ÑÐ¸ Ð¸ Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½ Ð¿ÑÐµÐ´Ð²Ð°ÑÐ¸ÑÐµÐ»ÑÐ½ÑÐ¹ Ð°Ð½Ð°Ð»Ð¸Ð· Ð½Ð°Ð±Ð¾ÑÐ° Ð´Ð°Ð½Ð½ÑÑ. Ð ÑÑÐµÑÑÐµÐ¹ Ð³Ð»Ð°Ð²Ðµ Ð¿ÑÐµÐ´ÑÑÐ°Ð²Ð»ÐµÐ½Ñ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÑ ÑÐ°Ð±Ð¾ÑÑ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ñ Ð¸ Ð¾ÑÐµÐ½ÐºÐ° ÐºÐ°ÑÐµÑÑÐ²Ð° Ð¿Ð¾Ð»ÑÑÐµÐ½Ð½ÑÑ Ð¼Ð¾Ð´ÐµÐ»ÐµÐ¹.
description: The object of the study: a set of data collected by phthisiologists during the initial examination of a patient with a confirmed diagnosis of Tuberculosis. The purpose of this work is to develop a medical information system based on the results of clinical trials and the use of machine learning algorithms for analyzing a data set. This work includes three chapters. The first chapter describes the subject area of this work, current problems in the field of infectious diseases. Examples of how machine learning can contribute to the automation of some processes in medicine are considered. The classification problem and methods of its solution are described. In the second chapter, the main methods for solving the binary classification problem are considered, algorithms for solving the problem are described and a preliminary analysis of the data set is carried out. The third chapter presents the results of the program and the evaluation of the quality of the obtained models.