medalphabetМедицинский алфавитMedical alphabet2078-56312949-2807ООО «Альфмед»10.33667/2078-5631-2022-12-27-33medalphabet-2676Research ArticleСтатьиИскусственный интеллект в диагностике хронического гастрита, инфекции Helicobacter pylori и функциональной диспепсииArtificial intelligence in diagnostic of chronic gastritis, Helicobacter pylori infection and functional dyspepsiahttps://orcid.org/0000-0001-6434-1267УспенскийЮ. П.UspenskiyYu. P.

Успенский Юрий Павлович, д.м.н., проф., зав. кафедрой факультетской терапии имени В. А. Вальдмана; проф. кафедры внутренних болезней стоматологического факультета

Санкт-Петербург

Uspenskiy Yury P., DM Sci (habil.), professor, head of Dept of Faculty Therapy n.a. V. A. Valdman; professor at Dept of Internal Diseases of Stomatological Faculty

Saint Petersburg

uspenskiy65@mail.ruhttps://orcid.org/0000-0001-7429-0336БарышниковаН. В.BaryshnikovaN. V.

Барышникова Наталья Владимировна, к.м.н., доцент, м.н.с. лаборатории медико-социальных проблем педиатрии;, доцент кафедры внутренних болезней стоматологического факультета; н.с. лаборатории молекулярной микробиологии

Санкт-Петербург

Baryshnikova Natalia V., PhD Med, associate professor, junior science researcher of Laboratory of Medico-Social Pediatric Problems; associate professor of Dept of Internal Diseases of Stomatological Faculty; researcher at Laboratory of Molecular Microbiology

Saint Petersburg

baryshnikova_nv@mail.ruhttps://orcid.org/0000-0002-5369-4507ЕршоваА. А.ErshovaA. A.

Ершова Анастасия Андреевна, студентка VI курса

Екатеринбург

Ershova Anastasia A., 6th year student

Yekaterinburg

nastua_ershova@mail.ruФГБОУ ВО «Санкт-Петербургский государственный педиатрический медицинский университет» Минздрава России; ФГБОУ ВО «Первый Санкт-Петербургский государственный медицинский университет имени академика И. П. Павлова» Минздрава РоссииРоссияSaint Petersburg State Pediatric Medical University; First Saint Petersburg State Medical University n.a. academician I. P. PavlovRussian FederationФГБОУ ВО «Санкт-Петербургский государственный педиатрический медицинский университет» Минздрава России; ФГБОУ ВО «Первый Санкт-Петербургский государственный медицинский университет имени академика И. П. Павлова» Минздрава России; ФГБНУ «Институт экспериментальной медицины»РоссияSaint Petersburg State Pediatric Medical University; First Saint Petersburg State Medical University n.a. academician I. P. Pavlov; Institute of Experimental MedicineRussian FederationФГБОУ ВО «Уральский государственный медицинский университет» Минздрава РоссииРоссияUral State Medical UniversityRussian Federation202220062022012Практическая гастроэнтерология (1)2733Copyright © Успенский Ю.П., Барышникова Н.В., Ершова А.А., 20222022Успенский Ю.П., Барышникова Н.В., Ершова А.А.Uspenskiy Y.P., Baryshnikova N.V., Ershova A.A.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.med-alphabet.com/jour/article/view/2676

Заболевания верхних отделов пищеварительного тракта являются чрезвычайно распространенной патологией и имеют не только медицинское, но и социальное значение, так как часто возникают у молодых людей трудоспособного возраста. В статье представлен обзор современных данных литературы о возможностях искусственного интеллекта в диагностике и лечении хронического гастрита, в том числе с признаками атрофии, инфекции Helicobacter pylori и функциональной диспепсии. Собраны данные различных исследований, демонстрирующие эффективность работы различных нейронных сетей в диагностике этих заболеваний.

Diseases of the upper digestive tract are an extremely common pathology and have not only medical, but also social significance, because they often occur in young people of working age. The article presents an overview of current literature data on the capabilities of artificial intelligence in the diagnosis and treatment of chronic gastritis, including those with signs of atrophy, Helicobacter pylori infection and functional dyspepsia. Collected data from various studies demonstrating the effectiveness of different neural networks in the diagnosis of these diseases.

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