kaz44Вестник Университета Шакарима. Серия технические наукиBulletin of Shakarim University. Technical Sciences2788-79953006-0524«Шәкәрім университеті» КеАҚ10.53360/2788-7995-2026-2(22)-12kaz44-2478Research ArticleАВТОМАТИЗАЦИЯ И ИНФОРМАЦИОННЫЕ ТЕХНОЛОГИИИССЛЕДОВАНИЕ МЕТОДОВ ПЕРСОНАЛИЗИРОВАННОЙ МЕДИЦИНЫ С ПРИМЕНЕНИЕМ БАЙЕСОВСКОГО АНАЛИЗАRESEARCH OF PERSONALIZED MEDICINE METHODS USING BAYESIAN ANALYSIShttps://orcid.org/0000-0002-4072-3671ШаяхметоваА. С.ShayakhmetovaA. S.

Асем Серикбаевна Шаяхметова – PhD, и.о. профессора кафедры искусственного интеллекта и Big Data, 

050040, г. Алматы, проспект Аль-Фараби, 71

Asem Serikbayevna Shayakhmetova – PhD, Acting Professor, Department of Artificial Intelligence and Big Data, 

050040, Almaty, Al-Farabi Avenue, 71

asemshayakhmetova@mail.ruhttps://orcid.org/0000-0002-0511-7000ТасболатұлыН.TasbolatulyN.

Нұрболат Тасболатұлы – PhD, ассоциированный профессор Высшей школы информационных технологий и инженерии, 

010000, г. Астана, проспект Кабанбай батыра, 8 

Nurbolat Tasbolatuly  – PhD, Associate Professor, Higher School of Information Technology and Engineering, 

010000, Astana, Qabanbay Batyr Avenue, 8

nurbolat.tasbolatuly@aiu.edu.kzhttps://orcid.org/0000-0003-4690-8180ДосановН. Е.DosanovN. E.

Нурбай Ермаханович Досанов – докторант Высшей школы информационных технологий и инженерии, 

010000, г. Астана, проспект Кабанбай батыра, 8

Nurbay Ermakhanovich Dosanov – PhD student, Higher School of Information Technology and Engineering, 

010000, Astana, Qabanbay Batyr Avenue, 8

nurbaidos@gmail.comhttps://orcid.org/0009-0009-6623-783XОтманМ.OthmanM.

Мохаммед Отман – PhD, профессор,

43400 ЮПМ Серданг, Селангор

Mohammed Othman – PhD, Professor, 

43400 UPM Serdang, Selangor

https://orcid.org/0009-0003-9281-2574КүрішбайН.KurishbayN.

Нурбол Алгабекович Куришбай – докторант кафедры искусственного интеллекта и Big Data,

050040, г. Алматы, проспект Аль-Фараби, 71

Nurbol Algabekovich Kurishbay – PhD student, Department of Artificial Intelligence and Big Data, 

050040, Almaty, Al-Farabi Avenue, 71

kurishbaynurbol@gmail.comКазахский национальный университет имени аль-ФарабиКазахстанAl-Farabi Kazakh National UniversityKazakhstanМеждународный университет АстанаКазахстанAstana International UniversityKazakhstanПутра Малайзия университетМалайзияUniversiti Putra MalaysiaMalaysia20262907202602(22)114123Copyright © Шаяхметова А.С., Тасболатұлы Н., Досанов Н.Е., Отман М., Күрішбай Н., 20262026Шаяхметова А.С., Тасболатұлы Н., Досанов Н.Е., Отман М., Күрішбай Н.Shayakhmetova A.S., Tasbolatuly N., Dosanov N.E., Othman M., Kurishbay N.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://tech.vestnik.shakarim.kz/jour/article/view/2478

Статья посвящена изучению методов персонализированной медицины с использованием байесовского анализа. В современной медицине принятие эффективных решений с учетом генетических, клинических и образа жизни каждого пациента становится одним из важнейших подходов. В связи с этим особое применение имеют вероятностные подходы к анализу данных в условиях неопределенности. В работе рассматриваются возможности оценки вероятности развития заболеваний и оптимизации стратегий лечения путем объединения различных источников медицинских данных. Байесовский метод сочетает в себе предварительные знания и новую клиническую информацию. Тем самым позволяет повысить точность постановки диагноза и оценить риски. В исследовании анализируются эффективные способы поддержки процесса принятия медицинских решений с использованием вероятностных моделей. Также определяется практическая значимость персонифицированного подхода. В том числе рассматриваются вопросы ранней диагностики и персонализации лечения. Предлагаемый метод позволяет повысить качество обработки медицинских данных. Направлен на развитие правил персонализированной медицины.

The article is devoted to the research of personalized medicine methods using Bayesian analysis. In modern medicine, one of the most important ways is to make effective decisions taking into account the genetic, clinical and lifestyle characteristics of each patient. In this regard, probabilistic approaches to data analysis in conditions of uncertainty have a special application. The research examines the possibilities of assessing the likelihood of developing diseases and optimizing treatment strategies by combining various sources of medical data. The Bayesian method combines preliminary knowledge and new clinical information. Thus, it allows you to increase the accuracy of diagnosis and assess risks. The study analyzes effective ways to support the medical decision-making process using probabilistic models. At the same time, the practical significance of a personalized approach in medicine is revealed. In particular, the issues of early diagnosis and individualization of treatment are considered. The presented method allows you to improve the quality of medical data processing. Aimed at developing the rules of personalized medicine.

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The authors declare that there are no conflicts of interest present.