UDC 378:004.8:614.2

DOI: http://doi.org/10.15350/2409-7616.2022.3.20

Ivanchuk O.V.¹ (Astrakhan, Russian Federation) – olgaiva@astgmu.ru, Plashchevaya E.V.² (Blagoveshchensk, Russian Federation) – elena-plashhevaja@rambler.ru, Nurmukhambetova S.A.³ (Astrakhan, Russian Federation) – svet.nurmuhambetova2011@yandex.ru

¹Astrakhan State Medical University

²Amur State Medical Academy

³Astrakhan State Technical University

Abstract. Artificial intelligence (AI) occupies firmer positions in different spheres of science, technique and practical activity of humans, including medicine. Using huge data masses as well as neural networks integrated into fuzzy logic, AI finds its application in solving tasks on recognizing medical images, maintaining patient monitoring, building various mathematical models of medical biological models. In spite of the wide opportunities of AI in the field of medicine and healthcare, academic communities and practicing doctors recognize the issues of its implementation into practical activity of doctors and its potential risks. One of these issues emphasized by a number of researchers is the unwillingness of practicing doctors to implement AI for solving professional tasks. In the framework of our study, we considered it important to find out how well the doctors, the teaching staff of a medical university and the learners (students and interns) are aware of AI, whether they realize risks and problems connected with its implementation into medicine. For this purpose, we used a questionnaire, having estimated its reliability by calculating the α-Cronbach coefficient (α=0,847). Generalization of the results enabled us to answer the questions posed during the study, as well as to determine the correlation dependencies between the work experience of clinical practice and the level of knowledge in the field of AI, recognizing a number of problems and risks. The obtained results allowed us to map out the ways of solving the revealed issues by means of developing educational programs for practicing doctors, university teachers and students. These educational programs allow to harmoniously combine the knowledge in the field of AI with medical-biological, clinical researches, new methods of treatment algorithms and diagnostics.

Keywords: artificial intelligence in medicine, teaching bases of artificial intelligence to medical staff.

References:

1. Ryazanova S.V., Mazaev V.P., Komkov A.A. New trends in the formation of artificial intelligence in medicine. CardioSomatika, 2021, vol. 12, no.4, pp. 227-233. (In Russian).  DOI: https://doi.org/10.17816/22217185.2021.4.201264
2. Koshelev K.A., Edigaryan D.A. Prospects for the development of virtual reality technologies in dental education (literature review). Bulletin of New Medical Technologies, 2022, no. 29 (2), pp.27-31. (In Russian). DOI: https://doi.org/10.24412/1609-2163-2022-2-27-31
3. Lohani M., Al-Jamali D., Aljaaf A. Application of artificial intelligence technology in healthcare: a systematic reviewof. 2019. pp. 249-261. DOI: https://doi.org/10.1007/978-3-03038752-5_20
4. Rajkomar A., Dean J., Kohane I. Machine Learning in Medicine. International Journal of Medical Informatics, 2019, no. 380(14), pp.1347-1358. DOI: https://doi.org/10.1056/NEJMra1814259 
5. Ramesh A., Kabhati C., Monson J. Artificial Intelligence in Medicine. Chronicle of the Royal College of England, 2004, no. 86 (5), pp. 334-338 DOI: https://doi.org/10.1308/147870804290 
6. Hamet P., Trimbley J. Artificial intelligence in medicine. Metabolism. 2017, no. 69. pp.36-40. DOI: https://doi.org/10.1016/j.metabol.2017.01.011
7. Komorowski M, Celi LA. Will Artificial Intelligence Contribute to Overuse in Healthcare? Crit Care Med, 2017, no. 45(5), pp.912-913. DOI: https://doi.org/10.1097/CCM.0000000000002351
8. Plessas A. Computer simulation of virtual reality in preclinical dentistry: can a computer simulator replace conventional dental phantoms and faculty supervision ? Medical education and professional development, 2018, no. 1 (31), pp.56-70. (In Russian). EDN: URLSSU URL: https://www.elibrary.ru/item.asp?id=35086015
9. Gantsev Sh. H., Franz M.V. Artificial intelligence as a support tool in making decisions on the diagnosis of cancer. Medical Bulletin of Bashkortostan, 2018, no. 13 (76). pp. 67-71. EDN: YPUTVB URL: https://www.elibrary.ru/item.asp?id=36546572
10. Boillat T., Nawaz F.A., Rivas H. Readiness to Embrace Artificial Intelligence Among Medical Doctors and Students: Questionnaire-Based Study. JMIR Med Educ, 2022, vol. 8, no.12.  e34973. DOI: https://doi.org/10.2196/34973
11. Park Si J., Siegel L. Perspectives of medical students on the impact of artificial intelligence on the practice of medicine. Modern problems in diagnostic radiology, 2021,no. 50 (5). pp.614-619. DOI: https://doi.org/10.1067/j.cpradiol.2020.06.011
12. Fomina E.E. Review of methods for assessing the reliability of the measuring scale in sociological research. Economics. Sociology. Right, 2018, no. 4 (12), pp.63-70. (In Russian). EDN: YWJGMP URL: https://www.elibrary.ru/item.asp?id=36921133
13. Lomis K., JeffriesP., PalattaA. Artificial Intelligence for Teachers of Medical Specialties. Washington, National Academy of Medicine Publ., 2017. DOI: https://doi.org/10.31478/202109a
14. Masters K. Artificial intelligence in medical education. Medical education, 2019, no. 41 (9), pp.976-980. DOI: https://doi.org/10.1080/0142159X.2019.1595557
15. Hosny A., Parmar C., Quackenbush J., Schwartz L.H.. Artificial intelligence in radiology. Nature Reviews Cancer, 2018, no. 18(8), pp. 500-510. DOI: https://doi.org/10.1038/s41568-018-0016-5  
16. Itinson K.S. Artificial intelligence as a promising technology in the field of medical education and medicine. Karelian Scientific Journal, 2020, no. 9 (2(31), pp. 16-18. (In Russian). URL: https://elibrary.ru/item.asp?id=42987611

For citation:

Ivanchuk O.V., Plashchevaya E.V., Nurmukhambetova S.A. Artificial intelligence in the system of healthcare: issues if readiness and education. CITISE, 2022, no. 3, pp. 225-237. DOI: http://doi.org/10.15350/2409-7616.2022.3.20