Sociology of MedicineSociology of MedicineСоциология медицины1728-28102413-2942Eco-Vector61913210.17816/socm619132HEALTHCARE DIGITALIZATIONЦИФРОВИЗАЦИЯ ЗДРАВООХРАНЕНИЯResearch ArticleProblematic aspects of medical artificial intelligence. Part 1Проблемы медицинского искусственного интеллекта. Часть 1https://orcid.org/0000-0003-3211-08998316-7111BerdutinVitalii A.БердутинВиталий Анатольевич
Russian Federation

MD, Cand. Sci. (Medicine)

канд. мед. наук

vberdt@gmail.comhttps://orcid.org/0000-0001-6328-079X4943-6121RomanovaTatyana E.РомановаТатьяна Евгеньевна
Russian Federation

MD, Cand. Sci. (Medicine)

канд. мед. наук

drmedromanova@gmail.comhttps://orcid.org/0000-0002-1815-54369014-6344RomanovSergey V.РомановСергей Владимирович
Russian Federation

MD, Dr. Sci. (Medicine)

д-р мед. наук

director@pomc.ruhttps://orcid.org/0000-0001-7403-77445602-2435AbaevaOlga P.АбаеваОльга Петровна
Russian Federation

MD, Dr. Sci. (Medicine), Professor

д-р мед. наук, проф.

abaevaop@inbox.ruState Research Center — Burnasyan Federal Medical Biophysical Center of Federal Medical Biological AgencyГосударственный научный центр Российской Федерации — Федеральный медицинский биофизический центр имени А.И. БурназянаPrivolzhsky Research Medical UniversityПриволжский исследовательский медицинский университетPrivolzhsky District Medical Center of the Federal Medical and Biological AgencyПриволжский окружной медицинский центр Федерального медико-биологического агентстваState Research Center — Burnasyan Federal Medical Biophysical Center of Federal Medical Biological AgencyГосударственный научный центр Российской Федерации — Федеральный медицинский биофизический центр имени А.И. Бурназяна13062024151220232222022112510202328102023Copyright ©; 2023, Eco-VectorCopyright ©; 2023, Эко-Вектор2023Eco-VectorЭко-Векторhttps://eco-vector.com/for_authors.php#07https://rjsocmed.com/1728-2810/article/view/619132

BACKGROUND: Artificial intelligence, like medicine, is a dynamically developing field that can be considered both a science and an art. This makes it much more difficult to use artificial intelligence compared to other technologies that come with a user manual.

Research and start-ups in the field of medical artificial intelligence are rapidly multiplying: the popularity of smart mobile devices, networked applications and remote digital services is growing. However, there are still some problems that complicate the widespread use of artificial intelligence algorithms in everyday clinical practice. The reasons for this are the high cost of operating neural network platforms and the limited qualifications of some medical professionals in the field of computer technology. These are only temporary difficulties, though, which should and will be gradually resolved.

CONCLUSION: This article focuses on the most sensitive points that are currently hindering the accelerated progress of machine learning in healthcare.

Обоснование. Медицинский искусственный интеллект — динамично развивающееся направление, к которому нужно относиться не только как к науке, но и как к искусству. Это значительно усложняет эксплуатацию искусственного интеллекта по сравнению с компьютерными программами, снабжаемыми пользовательской инструкцией.

Инновации в области медицинского искусственного интеллекта стремительно множатся: растет популярность умных мобильных устройств, сетевых приложений и удаленных цифровых сервисов. Однако существует ряд серьезных проблем, затрудняющих широкое использование алгоритмов искусственного интеллекта в повседневной клинической практике. Причинами сложностей являются высокая стоимость разработки нейросетевых платформ и недостаточный уровень квалификации медицинского персонала в области цифровых технологий. Однако есть веские основания полагать, что данные трудности со временем будут постепенно преодолеваться.

Заключение. В данной статье рассмотрены наиболее проблемные аспекты, препятствующие прогрессу технологий машинного обучения в здравоохранении.

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