perinatologyРоссийский вестник перинатологии и педиатрииRossiyskiy Vestnik Perinatologii i Pediatrii (Russian Bulletin of Perinatology and Pediatrics)1027-40652500-2228Ltd. “The National Academy of Pediatric Science and Innovation”10.21508/1027-4065-2017-62-6-16-22perinatology-586Research ArticleПЕРСОНАЛИЗИРОВАННАЯ ПЕДИАТРИЯPERSONALIZED PEDIATRICSПЕРСОНАЛИЗИРОВАННАЯ МЕДИЦИНА: ГЕНОМ, ЭЛЕКТРОННОЕ ЗДРАВООХРАНЕНИЕ И ИНТЕЛЛЕКТУАЛЬНЫЕ СИСТЕМЫ. ЧАСТЬ 2. МОЛЕКУЛЯРНАЯ ГЕНЕТИКА И МЕТОДЫ ИНТЕЛЛЕКТУАЛЬНОГО АНАЛИЗАPERSONALIZED MEDICINE: GENOME, ELECTRONIC HEALTH AND INTELLIGENT SYSTEMS. PART 2. MOLECULAR GENETICS AND METHODS OF INTELLECTUAL ANALYSIShttps://orcid.org/0000-0002-3459-8851КобринскийБ. А.KobrinskiiB. A.

Кобринский Борис Аркадьевич – доктор медицинских наук, профессор, зав. лабораторией систем поддержки принятия клинических решений.

Институт современных информационных технологий в медицине Федерального исследовательского центра «Информатика и управление» РАНРоссияInstitute of Modern Information Technologies in Medicine, Federal Research Center “Computer Science and Control”Russian Federation2017110120186261622Copyright © Ltd. “The National Academy of Pediatric Science and Innovation”, 20182018Ltd. “The National Academy of Pediatric Science and Innovation”Ltd. “The National Academy of Pediatric Science and Innovation”https://www.ped-perinatology.ru/jour/about/submissions#copyrightNoticehttps://www.ped-perinatology.ru/jour/article/view/586

Переход к персонализированной медицине в практическом плане должен сочетать исследование проблемы молекулярно-генетической предрасположенности к заболеваниям с анализом переходных состояний в организме в направлении возможной  патологии. Классификация и контроль состояния могут эффективно осуществляться с использованием методов искусственного интеллекта. Рассматриваются различные интеллектуальные подходы в разных условиях контроля за пациентами.

The transition to personalized medicine in practical terms should combine the problems of molecular-genetic predisposition to diseases with transient states in the organism in the direction of possible pathology. Classification and monitoring of the state can be  effectively carried out using artificial intelligence methods. Various intellectual approaches are considered in different conditions for  monitoring patient.

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