Standardization in regulating artificial intelligence systems in Russian healthcare
V. V. Zinchenko , A N Khoruzhaya , D E. Sharova , E S Akhmad , O A Mokienko , A V Vladzymyrskyy , S P Morozov
Kazan medical journal ›› 2021, Vol. 102 ›› Issue (6) : 923 -933.
Standardization in regulating artificial intelligence systems in Russian healthcare
Artificial intelligence technologies in medical practice are a promising direction in the world. Artificial intelligence medical decision support systems, diagnostic and screening programs can help medical personnel in routine and complex tasks and improve the level of medical care provided to patients. At the same time, the development, production and distribution of artificial intelligence systems must be regulated without fail. Registration and subsequent control (post-registration monitoring) of artificial intelligence systems in medicine require the creation, adjustment of the legal framework and technological regulation. The Russian Federation has developed a promising development strategy in this area. Seven national standards have been developed by experts in the field of Artificial intelligence in healthcare. These standards establish the procedures for conducting clinical and technical trials, performance requirements and the concept of life cycle, a quality management system and risk management. A separate standards is devoted to dataset creation for training and testing the developed algorithms, requirements for them and a metadata format. There are plans to bring the developed national standards to the international level, which will allow Russian manufacturers of artificial intelligence systems implemented these national standards to comply with foreign counterparts and become more competitive at the international level. The international community has already supported the development of an ISO standard based on the national standard for clinical trials. The development will be performed based on the technical committee ISO/TC 215 (Health informatics) in conjunction with ISO/IEC JTC 1/SC 42 (Artificial intelligence), this will allow bringing the national requirements for the Artificial intelligence to the international level. The cycle of these standards will summarize recognized methodologies, helping both manufacturers and medical organizations, doctors and patients to produce and use a quality, safe and effective product.
standardization / medical artificial intelligence / artificial intelligence-based software as a medical device / medical software
| [1] |
Meldo A.A., Utkin L.V., Moiseyenko V.M. XXI century diagnostic algorithms. Artifitial intelligance in lung cancer detection. Prakticheskaya onkologiya. 2018; 19 (3): 292–298. (In Russ.) DOI: 10.31917/1903292. |
| [2] |
Мелдо А.А., Уткин Л.В., Моисеенко В.М. Алгоритмы диагностики XXI века. Искусственный интеллект в распознавании рака лёгкого. Практич. онкол. 2018; 19 (3): 292–298. DOI: 10.31917/1903292. |
| [3] |
Borodulina E.A. Artificial intelligence in tuberculosis detection. Opportunities and prospects. The Doctor. 2020; 31 (5): 30–33. (In Russ.) DOI: 10.29296/25877305-2020-05-06. |
| [4] |
Бородулина Е.А. Искусственный интеллект в выявлении туберкулёза: возможности и перспективы. Врач. 2020; 31 (5): 30–33. DOI: 10.29296/25877305-2020-05-06. |
| [5] |
Castaldi P.J., Boueiz A., Yun J., Estepar R.S.J., Ross J.C., Washko G., Cho M.H., Hersh C.P., Kinney G.L., Young K.A., Regan E.A., Lynch D.A., Criner G.J., Dy J.G., Rennard S.I., Casaburi R., Make B.J., Crapo J., Silverman E.K., Hokanson J.E.; COPDGene Investigators. Machine Learning characterization of COPD Subtypes: insights from the COPDGene Study. Chest. 2020; 157.5: 1147–1157. DOI: 10.1016/j.chest.2019.11.039. |
| [6] |
Retson T.A., Eghtedari M. Computer-Aided detection/diagnosis in breast imaging: a focus on the evolving FDA regulations for using software as a medical device. Curr. Radiol. Rep. 2020; 8: 7. DOI: 10.1007/s40134-020-00350-6. |
| [7] |
Gusev A.V., Gavrilov D.V., Korsakov I.N., Serova L.M., Novitsky R.E., Kuznetsova T.Yu. Prospects for the use of machine learning methods for predicting cardiovascular disease. Vrach i informatsionnye tekhnologii. 2019; (3): 41–47. (In Russ.) |
| [8] |
Гусев А.В., Гаврилов Д.В., Корсаков И.Н., Серова Л.М., Новицкий Р.Э., Кузнецова Т.Ю. Перспективы использования методов машинного обучения для предсказания сердечно-сосудистых заболеваний. Врач и информ. технологии. 2019; (3): 41–47. |
| [9] |
He J., Baxter S.L., Xu J., Xu J., Zhou X., Zhang K. The practical implementation of artificial intelligence technologies in medicine. Nat. Med. 2019; 25: 30–36. DOI: 10.1038/s41591-018-0307-0. |
| [10] |
Ranschaert E.R., Morozov S.P., Algra P.R. Artificial Intelligence in Medical Imaging. 1st ed. Springer International Publishing. 2019; 373 p. DOI: 10.1007/978-3-319-94878-2. |
| [11] |
Gusev A.V., Dobridnyuk S.L. Artificial intelligence in medicine and healthcare. Informatsionnoe obshchestvo. 2017; (4–5): 78–93. (In Russ.) |
| [12] |
Гусев А.В., Добриднюк С.Л. Искусственный интеллект в медицине и здравоохранении. Информационное общество. 2017; (4–5): 78–93. |
| [13] |
Kurakova N.G., Tsvetkova L.A., Cherchenko O.V. Artificial intelligence technologies in medicine and healthcare: Russia's position on the global patent and publication landscape. Vrach i informatsionnye tekhnologii. 2020; (2): 81–100. (In Russ.) DOI: 10.37690/1811-0193-2020-2-81-100. |
| [14] |
Куракова Н.Г., Цветкова Л.А., Черченко О.В. Технологии искусственного интеллекта в медицине и здравоохранении: позиции России на глобальном патентном и публикационном ландшафте. Врач и информ. технологии. 2020; (2): 81–100. DOI: 10.37690/1811-0193-2020-2-81-100. |
| [15] |
Meldo A.A., Utkin L.V., Trofimova T.N. Artificial intelligence in medicine: current state and main directions of development of the intellectual diagnostics. Luchevaya diagnostika i terapiya. 2020; (1): 9–17. (In Russ.) DOI: 10.22328/2079-5343-2020-11-1-9-17. |
| [16] |
Мелдо А.А., Уткин Л.В., Трофимова Т.Н. Искусственный интеллект в медицине: современное состояние и основные направления развития интеллектуальной диагностики. Лучевая диагностика и терапия. 2020; (1): 9–17. DOI: 10.22328/2079-5343-2020-11-1-9-17. |
| [17] |
Lebedev G.S., Fomina I.V., Shaderkin I.A., Lisnenko A.A., Ryabkov I.V., Kachkovskiy S.V., Melaev D.V. Main directions for development of internet-technologies in health care (systematic review). Social aspects of population health. 2017; 57 (5): 10. (In Russ.) DOI: 10.21045/2071-5021-2017-57-5-10. |
| [18] |
Лебедев Г.С., Фомина И.В., Шадеркин И.А., Лисненко А.А., Рябков И.В., Качковский С.В., Мелаев Д.В. Основные направления развития интернет-технологий в здравоохранении (систематический обзор). Социал. аспекты здоровья населения. 2017; 57 (5): 10. DOI: 10.21045/2071-5021-2017-57-5-10. |
| [19] |
Karpov O.E., Klimenko G.S., Lebеdev G.S. Application of intelligent systems in health care. Modern high technologies. 2016; (7-1): 38–43. (In Russ.) |
| [20] |
Карпов О.Э., Клименко Г.С., Лебедев Г.С. Применение интеллектуальных систем в здравоохранении. Соврем. наукоёмкие технол. 2016; (7-1): 38–43. |
| [21] |
Gusev A.V., Zarubina T.V. Clinical Decisions Support in medical information systems of a medical organization. Vrach i informatsionnye tekhnologii. 2017; (2): 60–72. (In Russ.) |
| [22] |
Гусев А.В., Зарубина Т.В. Поддержка принятия врачебных решений в медицинских информационных системах медицинской организации. Врач и информ. технол. 2017; (2): 60–72. |
| [23] |
Elenko E., Speier A., Zohar D. A regulatory framework emerges for digital medicine. Nat. Biotechnol. 2015; 33: 697–702. DOI: 10.1038/nbt.3284. |
| [24] |
Hwang T.J., Kesselheim A.S., Vokinger K.N. Lifecycle regulation of artificial intelligence — and machine learning-based software devices in medicine. JAMA. 2019; 322 (23): 2285–2286. DOI: 10.1001/jama.2019.16842. |
| [25] |
Goodman K.W. Ethics in health informatics. Yearbook of medical informatics. 2020; 29 (1): 26–31. DOI: 10.1055/s-0040-1701966. |
| [26] |
Andreeva I.L., Natenzon M.Y. Priorities for the development of innovative digital healthcare in Russia. Health care standardization problems. 2017; (11–12): 3–9. (In Russ.) DOI: 10.26347/1607-2502201711-12003-009. |
| [27] |
Андреева И.Л., Натензон М.Я. Первоочередные задачи развития инновационного цифрового здравоохранения России. Пробл. стандартизации в здравоохр. 2017; (11–12): 3–9. DOI: 10.26347/1607-2502201711-12003-009. |
| [28] |
IMDRF/SaMD WG/N41FINAL: 2017. Software as a Medical Device (SaMD): Clinical Evaluation. http://www.imdrf.org/docs/imdrf/final/technical/imdrf-tech-170921-samd-n41-clinical-evaluation_1.pdf (access date: 02.09.2021). |
| [29] |
Regulatory Guidelines for Software Medical Devices — A Life Cycle Approach. April 2020. Singapore. https://www.hsa.gov.sg/docs/default-source/announcements/regulatory-updates/regulatory-guidelines-for-software-medical-devices--a-lifecycle-approach.pdf (access date: 02.09.2021). |
| [30] |
FDA. Proposed Regulatory Framework for Modifications to Artificial Intelligence/Machine Learning (AI/ML)-Based Software as a Medical Device (SaMD) — Discussion Paper and Request for Feedback. https://www.kslaw.com/attachments/000/007/073/original/7-1-19_Intellectual_Property___Technology_Law_Journal.pdf?1562866795 (access date: 02.09.2021). |
| [31] |
The National Artificial Intelligence Research and Development Strategy Plan (2016–2019). https://www.nitrd.gov/pubs/National-AI-RD-Strategy-2019.pdf (access date: 20.09.2021). |
| [32] |
Yaeger K.A., Martini M., Yaniv G., Oermann E.K., Costa A.B. United States regulatory approval of medical devices and software applications enhanced by artificial intelligence. Health Policy and Technology. 2019; 8 (2): 192–197. DOI: 10.1016/j.hlpt.2019.05.006. |
| [33] |
AI in Korea. https://www.oecd.ai/dashboards/countries/SouthKorea (access date: 20.09.2021). |
| [34] |
On artificial intelligence — A European approach to excellence and trust. https://ec.europa.eu/info/publications/white-paper-artificial-intelligence-european-approach-excellence-and-trust_en (access date: 20.09.2021). |
| [35] |
Schneeberger D., Stöger K., Holzinger A. The European Legal Framework for Medical AI. In: Lecture Notes in Computer Science. Vol. 12 279, Machine learning and knowledge extraction. 2020; 209–226. DOI: 10.1007/978-3-030-57321-8. |
| [36] |
In their own words — New Generation Artificial Intelligence Development Plan. https://www.airuniversity.af.edu/CASI/Display/Article/2521258/in-their-own-words-new-generation-artificial-intelligence-development-plan/ (access date: 20.09.2021). |
| [37] |
Reddy S., Allan S., Coghlan S., Cooper P. A governance model for the application of AI in health care. J. Am. Med. Inform. Assoc. 2020; 27 (3): 491–497. DOI: 10.1093/jamia/ocz192. |
| [38] |
Passport of the national program “Digital Economy of the Russian Federation” (approved by the Presidium of the Council under the President of the Russian Federation for Strategic Development and National Projects, minutes of December 24, 2018 No. 16). http://government.ru/info/35568/ (access date: 03.09.2021). DOI: http://dx.doi.org/10.2471/BLT.13.020813. |
| [39] |
Паспорт национальной программы «Цифровая экономика Российской Федерации» (утв. президиумом Совета при Президенте Российской Федерации по стратегическому развитию и национальным проектам, протокол от 24 декабря 2018 г. №16). http://government.ru/info/35568/ (дата обращения: 03.09.2021). DOI: http://dx.doi.org/10.2471/BLT.13.020813. |
| [40] |
The Order of the Federal Agency for Technical Regulation and Metrology №1732, issued at 25.07.2019 “On the creation of a technical committee for standardization “Artificial Intelligence””. http://www.consultant.ru/cons/cgi/online.cgi?req=doc&base=EXP&n=735452#4SISMoSvOiyks9EN (access date: 03.09.2021). (In Russ.) |
| [41] |
Приказ Росстандарта от 25 июля 2019 г. №1732 «О создании технического комитета по стандартизации “Искусственный интеллект”». http://www.consultant.ru/cons/cgi/online.cgi?req=doc&base=EXP&n=735452#4SISMoSvOiyks9EN (дата обращения: 03.09.2021). |
| [42] |
Order of the Technical Committee for Standardization ‘Artificial Intelligence” No. 1, issued at January 13, 2020 “On the definition of the basic organization of the subcommittee “Artificial Intelligence in Healthcare””. https://tele-med.ai/media/uploads/2021/03/18/01_-2-2.pdf (access date: 03.09.2021). (In Russ.) |
| [43] |
Приказ технического комитета по стандартизации «Искусственный интеллект» от 13 января 2020 г. №1 «Об определении базовой организации подкомитета “Искусственный интеллект в здравоохранении”». https://tele-med.ai/media/uploads/2021/03/18/01_-2-2.pdf (дата обращения: 03.09.2021). |
| [44] |
Decision of the Council of the Eurasian Economic Commission No. 29, issued at February 12, 2016 “On the rules for conducting clinical and clinical laboratory tests (research) of medical devices”. https://docs.eaeunion.org/docs/ru-ru/01410222/cncd_17052016_29 (access date: 20.09.2021). (In Russ.) |
| [45] |
Решение Совета Евразийской экономической комиссии от 12 февраля 2016 г. №29 «О правилах проведения клинических и клинико-лабораторных испытаний (исследований) медицинских изделий». https://docs.eaeunion.org/docs/ru-ru/01410222/cncd_17052016_29 (дата обращения: 20.09.2021). |
| [46] |
Decision of the Council of the Eurasian Economic Commission No. 28, issued at 12.02.2016 “On approval of the Rules for conducting technical tests of medical devices”. https://docs.eaeunion.org/docs/ru-ru/01410219/cncd_17052016_28 (access date: 20.09.2021). (In Russ.) |
| [47] |
Решение Совета Евразийской экономической комиссии от 12.02.2016 №28 «Об утверждении Правил проведения технических испытаний медицинских изделий». https://docs.eaeunion.org/docs/ru-ru/01410219/cncd_17052016_28 (дата обращения: 20.09.2021). |
| [48] |
Belousov D.Yu., Zyryanov S.K., Kolbin A.S. Upravlenie klinicheskimi issledovaniyami. (Clinical research management.) 1st ed. M.: Buki Vedi, Izdatel'stvo OKI. 2017; 676 p. (In Russ.) |
| [49] |
Белоусов Д.Ю., Зырянов С.К., Колбин А.С. Управление клиническими исследованиями. 1-е изд. М.: Буки Веди, Издательство ОКИ. 2017; 676 с. |
| [50] |
Pesapane F., Volonté C., Codari M., Sardanelli F. Artificial intelligence as a medical device in radiology: ethical and regulatory issues in Europe and the United States. Insights Imaging. 2018; 9: 745–753. DOI: 10.1007/s13244-018-0645-y. |
| [51] |
Marc D.K., Ronald M.S., Raymond G. Medical image data and datasets in the era of machine learning — whitepaper from the 2016 C-MIMI Meeting Dataset Session. J. Digit. Imaging. 2017; 30: 392–399. DOI: 10.1007/s10278-017-9976-3. |
| [52] |
Gerke S., Minssen T., Cohen G. Ethical and legal challenges of artificial intelligence-driven healthcare. In: Artificial Intelligence in Healthcare. Academic Press. 2020; 295–336. DOI: 10.1016/B978-0-12-818438-7.00012-5. |
| [53] |
Kupriyanovsky V.P., Yartsev D.I., Utkin N.A., Namiot D.E. Economy standards in the digital age and information and communication technologies on the example of the British Standards Institute. Intern. J. Open Inform. Technol. 2016; 4 (6): 1–9. (In Russ.) |
| [54] |
Куприяновский В.П., Ярцев Д.И., Уткин Н.А., Намиот Д.Е. Экономика стандартизации в цифровую эпоху и информационно-коммуникационные технологии на примере Британского института стандартов. Intern. J. Open Inform. Technol. 2016; 4 (6): 1–9. |
| [55] |
Gusev A.V., Pliss M.A. The basic recommendations for the creation and development of information systems in health care based on artificial intelligence. Vrach i informatsionnye tekhnologii. 2018; (3): 45–60. (In Russ.) |
| [56] |
Гусев А.В., Плисс М.А. Основные рекомендации к созданию и развитию информационных систем в здравоохранении на базе искусственного интеллекта. Врач и информ. технологии. 2018; (3): 45–60. |
Eco-Vector
/
| 〈 |
|
〉 |