title: ÐÑÐµÐ´ÑÐºÐ°Ð·Ð°ÑÐµÐ»ÑÐ½Ð°Ñ Ð¼Ð¾Ð´ÐµÐ»Ñ Ð¿ÑÐ¸ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ð¸ Ð·Ð°Ð²Ð¸ÑÐ¸Ð¼Ð¾ÑÑÐ¸ Ð³ÑÑÐ¿Ð¿ Ð·Ð°Ð±Ð¾Ð»ÐµÐ²Ð°Ð½Ð¸Ð¹ Ð¾Ñ Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÐ¾Ð² ÐºÑÐ¾Ð²Ð¸ Ð´Ð»Ñ Ð¼Ð¾Ð´ÑÐ»Ñ Ð¿Ð¾Ð´Ð´ÐµÑÐ¶ÐºÐ¸ Ð¿ÑÐ¸Ð½ÑÑÐ¸Ñ ÑÐµÑÐµÐ½Ð¸Ð¹ Ð² Ð¼ÐµÐ´Ð¸ÑÐ¸Ð½ÑÐºÐ¾Ð¹ Ð¸Ð½ÑÐ¾ÑÐ¼Ð°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹ ÑÐ¸ÑÑÐµÐ¼Ðµ
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: Predictive model in the study of the dependence of disease groups on blood parameters for the decision support module in the medical information system
Creators: name: ÐÐµÑÐ¾Ð½Ð¾Ð², Ð¡ÑÐµÐ¿Ð°Ð½
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: 2020
Subjects: Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
Ð¿ÑÐµÐ´ÑÐºÐ°Ð·Ð°ÑÐµÐ»ÑÐ½Ð°Ñ Ð¼Ð¾Ð´ÐµÐ»Ñ
python
Ð°Ð½Ð°Ð»Ð¸Ð·
Ð¿ÑÐµÐ¾Ð±ÑÐ°Ð·Ð¾Ð²Ð°Ð½Ð¸Ðµ Ð´Ð°Ð½Ð½ÑÑ
Ð¸Ð½ÑÐ¾ÑÐ¼Ð°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ¸ÑÑÐµÐ¼Ð°
Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÑ ÐºÑÐ¾Ð²Ð¸
Ð´Ð¸Ð°Ð³Ð½Ð¾Ð·
machine learning
predictive model
analysis
data transformation
information system
blood parameters
diagnosis

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description: This work is devoted to the study of the dependence of disease groups on blood parameters for the development of a predictive model for predicting disease group based on blood parameters. Tasks that were solved in the process of development: â¢ Review of the medical process; â¢ Review of the system into which the module with the predictive model will be integrated; â¢ Data analysis; â¢ Data conversion; â¢ Overview of machine learning models â¢ Select the machine learning model with the lowest error rate; The data for the development were obtained in an impersonal form, in accordance with Federal Law No. 152, from medical institutions of the city of Saint-Petersburg: City Hospital No. 3, City Children's Hospital No. 4 named St. Olga, Maternity Hospital No. 13; In this work the review of medical and laboratory information systems is made. A review of machine learning methods has been made. The work on analysis and transformation of data for application of machine learning methods was carried out. Machine learning methods for data have been applied. As a result, a comparative analysis of the results of the application of machine learning methods was carried out, namely a comparison of testing errors. As the result, the most suitable method of learning with the lowest testing error, k neighbors classifier, has been chosen.