Risks and limitations of using artificial intelligence in medicine
- Authors: Beregovykh V.V.1,2, Panteleev V.I.2, Shimanovsky N.L.2, Roitberg P.G.2
-
Affiliations:
- Russian Academy of Sciences
- Plekhanov Russian University of Economics
- Issue: Vol 80, No 3 (2025)
- Pages: 198-206
- Section: HEALTH CARE MANAGEMENT: CURRENT ISSUES
- Published: 10.10.2025
- URL: https://vestnikramn.spr-journal.ru/jour/article/view/18075
- DOI: https://doi.org/10.15690/vramn18075
- ID: 18075
Cite item
Abstract
The scientific, technical, ethical, and legal aspects of applying artificial intelligence (AI) in modern medicine, as well as its impact on medical professionals and patients, are examined. The research methodology is based on the analysis of scientific publications dedicated to the use of AI in medicine. Systematization of the available data allows identifying key limitations faced by developers of medical AI systems and their users. These issues are related to the quality and completeness of the data on which machine learning models are built, the limited clinical context, challenges in knowledge generalization, and system interoperability. Ethical challenges include concerns about privacy, algorithmic bias, and the distribution of responsibility. Additionally, there are issues regarding the regulatory framework for AI in healthcare and the training of medical professionals in computer technologies. Overcoming these limitations requires improving data quality, developing multimodal systems, increasing algorithm transparency, and refining the regulatory framework.
Full Text
About the authors
Valery V. Beregovykh
Russian Academy of Sciences; Plekhanov Russian University of Economics
Email: beregovykh@ramn.ru
ORCID iD: 0000-0002-0210-4570
SPIN-code: 5940-7554
PhD in Technical Sciences, Professor, Academician of the RAS
Russian Federation, Moscow; MoscowVladimir I. Panteleev
Plekhanov Russian University of Economics
Author for correspondence.
Email: vpantel@mail.ru
ORCID iD: 0000-0002-1575-1267
SPIN-code: 4095-8670
MD, PhD
Russian Federation, 36 Stremyanny per., 109992, MoscowNikolay L. Shimanovsky
Plekhanov Russian University of Economics
Email: shimann@yandex.ru
ORCID iD: 0000-0001-8887-4420
SPIN-code: 5232-8230
MD, PhD, Professor, Corresponding Member of the RAS
Russian Federation, MoscowPavel G. Roitberg
Plekhanov Russian University of Economics
Email: roitbergpg@rea.ru
ORCID iD: 0000-0002-9813-0385
PhD in Economics
Russian Federation, MoscowReferences
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