Метод оценки автономного программного обеспечения на основе технологий искусственного интеллекта для массовых профилактических исследований
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Научный журнал Моделирование, оптимизация и информационные технологииThe scientific journal Modeling, Optimization and Information Technology
Online media
issn 2310-6018

Method of evaluation of autonomous software based on artificial intelligence technologies for mass preventive studies

idZinchenko V.V., idErizhokov R.A., idArzamasov K.M.

UDC 004:614.2
DOI: 10.26102/2310-6018/2025.48.1.027

  • Abstract
  • List of references
  • About authors

The introduction of artificial intelligence (AI) technologies into medical practice requires a thorough assessment of their effectiveness, especially for systems operating autonomously. The method proposed in this study is based on a synthesis of the requirements of national standards in the field of medical AI developed by experts of the Scientific and Practical Clinical Center for Diagnostics and Telemedicine Technologies and data obtained as part of the "Moscow Experiment" on the introduction of innovative technologies. The testing was carried out on three AI software products used to analyze fluorographic studies in the period from January to May 2023. The evaluation included an analysis of the accuracy of algorithms (sensitivity, specificity), effectiveness in real clinical conditions, as well as a comparative analysis of the results with a quantitative interpretation of the data. The emphasis in the evaluation was on providing the AI system with a high level of diagnostic sensitivity, which will allow doctors to relieve themselves of routine monotonous work in mass preventive studies. The developed method demonstrated the possibility of a comprehensive assessment of autonomous AI systems, identifying differences in the effectiveness of products by key metrics. The proposed method allows systematizing the process of validating medical AI solutions, minimizing the risks of their incorrect use in autonomous operation. The results of the study can be used to standardize the assessment of AI tools in radiology and other areas of medicine that require a high level of diagnostic reliability.

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Zinchenko Victoria Valerevna

Email: ZinchenkoVV1@zdrav.mos.ru

ORCID |

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department

Moscow, Russian Federation

Erizhokov Rustam Arsenevich

ORCID |

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department
Moscow Institute of Physics and Technology; Federal State Autonomous Educational Institution of Higher Education I.M. Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation (Sechenov University)

Moscow, Russian Federation

Arzamasov Kirill Mikhailovich
Candidate of Medical Sciences, docent

ORCID |

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department
MIREA - Russian Technological University

Moscow, Russian Federation

Keywords: artificial intelligence in medicine, autonomous diagnostic systems, efficiency assessment, radiation diagnostics, radiology

For citation: Zinchenko V.V., Erizhokov R.A., Arzamasov K.M. Method of evaluation of autonomous software based on artificial intelligence technologies for mass preventive studies. Modeling, Optimization and Information Technology. 2025;13(1). URL: https://moitvivt.ru/ru/journal/pdf?id=1822 DOI: 10.26102/2310-6018/2025.48.1.027 .

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Full text in PDF

Received 14.02.2025

Revised 25.02.2025

Accepted 03.03.2025