farmaecFARMAKOEKONOMIKA. Modern Pharmacoeconomics and PharmacoepidemiologyФАРМАКОЭКОНОМИКА. Современная фармакоэкономика и фармакоэпидемиология2070-49092070-4933IRBIS LLC10.17749/2070-4909/farmakoekonomika.2024.267farmaec-1096Research ArticleREVIEW ARTICLESОБЗОРНЫЕ ПУБЛИКАЦИИArtificial intelligence: basic terms and concepts, the application in healthcare and clinical medicineИскусственный интеллект: основные термины и понятия, применение в здравоохранении и клинической медицинеhttps://orcid.org/0000-0001-7930-6018ЛамоткинА. И.LamotkinA. I.

Ламоткин Андрей Игоревич

2-я Брестская ул., д. 5, Москва 123056

ул. Добролюбова, д. 11, Москва 127254

Andrey I. Lamotkin

5 2nd Brestskaya Str., Moscow 123056

11 Dobrolyubov Str., Moscow 127254

https://orcid.org/0000-0002-0459-0488КорабельниковД. И.KorabelnikovD. I.

Корабельников Даниил Иванович, к.м.н., доцент

2-я Брестская ул., д. 5, Москва 123056

Daniil I. Korabelnikov, PhD, Assoc. Prof.

5 2nd Brestskaya Str., Moscow 123056

 

https://orcid.org/0000-0001-7707-441XЛамоткинИ. А.LamotkinI. A.

Ламоткин Игорь Анатольевич, д.м.н., проф.

Госпитальная пл., д. 3, Москва 105094

Волоколамское ш., д. 11, Москва 125080

Igor A. Lamotkin, Dr. Sci. Med., Prof. 

3 Gospitalnaya Sq., Moscow 105229

11 Volokolamskoe Shosse, Moscow 125080

ilamotkin@mail.ruАвтономная некоммерческая организация дополнительного профессионального образования «Московский медико-социальный институт им. Ф.П. Гааза»; Федеральное государственное бюджетное учреждение «Центральный научно-исследовательский институт организации и информатизации здравоохранения» Министерства здравоохранения Российской ФедерацииРоссияMoscow Haass Medical and Social Institute; Central Research Institute of Organization and Informatization of HealthcareRussian FederationАвтономная некоммерческая организация дополнительного профессионального образования «Московский медико-социальный институт им. Ф.П. Гааза»РоссияMoscow Haass Medical and Social InstituteRussian FederationФедеральное государственное бюджетное учреждение «Главный военный клинический госпиталь им. академика Н.Н. Бурденко» Министерства обороны Российской Федерации; Федеральное государственное бюджетное образовательное учреждение высшего образования «Российский биотехнологический университет (РОСБИОТЕХ)»РоссияBurdenko Main Military Clinical Hospital; Russian Biotechnological UniversityRussian Federation202405112024173409415Copyright © Lamotkin A.I., Korabelnikov D.I., Lamotkin I.A., 20242024Ламоткин А.И., Корабельников Д.И., Ламоткин И.А.Lamotkin A.I., Korabelnikov D.I., Lamotkin I.A.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.pharmacoeconomics.ru/jour/article/view/1096Objective

Objective: to explore the potential and challenges of artificial intelligence (AI) in clinical medicine and healthcare, and to determine the prospects for its implementation to improve diagnosis, treatment, and medical data management.

Material and methods

Material and methods. A literature review on the main terms and concepts of AI, its classification by application area, technologies, and methodologies was carried out. The learning methods such as supervised, unsupervised, and reinforcement learning were considered, as well as examples of AI application in various areas of medicine, including disease diagnosis and personalized medicine.

Results

Results. AI shows significant potential in improving diagnosis, optimizing treatment processes, and managing healthcare resources. Main application areas are related to medical image analysis, developing individualized treatment plans, and healthcare management. However, using AI faces challenges such as data availability and bias, fragmentation of systems, and complexity of algorithm interpretation.

Conclusion

Conclusion. Despite the existing challenges, the implementation of AI in medicine has great prospects, including improved diagnostic accuracy, reduced task completion time, and development of personalized medicine. It is important to consider the ethical aspects and the demand for further study of AI application in medicine to achieve the best results.

Цель

Цель: изучить возможности применения искусственного интеллекта (ИИ) в клинической медицине и здравоохранении, а также определить перспективы его внедрения для улучшения диагностики, лечения и управления медицинскими данными.

Материал и методы

Материал и методы. Проведен анализ литературы по основным терминам и понятиям ИИ, его классификации по области применения, технологиям и методологиям. Рассмотрены методы обучения, такие как обучение «с учителем», «без учителя» и с подкреплением, а также примеры использования ИИ в различных областях медицины, включая диагностику заболеваний и персонализированную медицину.

Результаты

Результаты. ИИ демонстрирует значительный потенциал в улучшении диагностики, оптимизации лечебных процессов и управлении ресурсами здравоохранения. Основные области применения связаны с анализом медицинских изображений, разработкой индивидуализированных планов лечения и управлением здравоохранением. Однако применение ИИ сталкивается с такими проблемами, как доступность и предвзятость данных, фрагментация систем и сложность интерпретации алгоритмов.

Заключение

Заключение. Несмотря на существующие сложности, внедрение ИИ в медицину имеет большие перспективы, включая улучшение точности диагностики, сокращение времени на выполнение задач и развитие персонализированной медицины. Важно учитывать этические аспекты и необходимость дальнейшего изучения применения ИИ в медицине для достижения наилучших результатов.

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