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3УДК 378.147
ARTIFICIAL INTELLIGENCE IN MEDICAL EDUCATION: PROMISE OR PITFALL?
AKIMOV MANAS ALMAZBEKOVICH
Postgraduate student, Department of General Surgery, Faculty of Medicine, Jalal-Abad State University named after B. Osmonov, Jalal-Abad, Kyrgyz Republic
MEDVEDEV IVAN SERGEEVICH
Student of the Faculty of Medicine, Jalal-Abad State University named after B. Osmonov, JalalAbad, Kyrgyz Republic
MEDVEDEV SERGEI NIKOLAYEVICH
Candidate of Sciences in Medicine, Associate Professor, of the Department of Propaedeutics and Family Medicine, Faculty of Medicine, Jalal-Abad State University named after B. Osmonov, JalalAbad city, Kyrgyz Republic
Abstract. The main task of higher medical school is to prepare a professional doctor who is capable of critical thinking and finding solutions in non-standard situations. The article discusses the digitalization of higher education and the inclusion of artificial intelligence tools in the pedagogical process. The purpose of this review is to assess the positive aspects of the digitalization of higher education and the possible risks of using artificial intelligence in higher education. The Internet and artificial intelligence platforms have serious capabilities for analyzing various information - medical records, laboratory tests, genome data, identifying the relationship between diseases and social factors. With the help of AI, it is possible to simulate a virtual patient with various pathologies to teach students diagnostic and treatment skills. However, there are concerns that the use of AI by students may raise ethical issues related to patient confidentiality, their informed consent for treatment, and AI bias in algorithmic decision-making. The authors focus on the method of teaching students at the patient's bedside as the most effective model for educating future doctors.
Key words: artificial intelligence, higher medical education, digital transformation, risks of using artificial intelligence in higher education, educational technologies, importance of clinical experience in medical education.
ИСКУССТВЕННЫЙ ИНТЕЛЛЕКТ В МЕДИЦИНСКОМ ОБРАЗОВАНИИ:
ОБЕЩАНИЕ ИЛИ ЛОВУШКА?
АКИМОВ МАНАС АЛМАЗБЕКОВИЧ
Аспирант кафедры общей хирургии лечебного факультета ЖАГУ им. Б. Осмонова, г.
Жалал-Абад, Кыргызская Республика
МЕДВЕДЕВ ИВАН СЕРГЕЕВИЧ
Студент лечебного факультета ЖАГУ им. Б. Осмонова, г. Жалал-Абад, Кыргызская
Республика
МЕДВЕДЕВ СЕРГЕЙ НИКОЛАЕВИЧ
Кандидат медицинских наук, доцент кафедры пропедевтики и семейной медицины лечебного факультета ЖАГУ им. Б. Осмонова, г. Жалал-Абад, Кыргызская
Республика
Аннотация Основная задача высшей медицинской школы - подготовить профессионального врача, способного критически мыслить и находить решения в
нестандартных ситуациях. В статье рассматривается цифровизация высшего образования и включение инструментов искусственного интеллекта в педагогический процесс. Целью данного обзора является оценка положительных сторон цифровизации высшего образования и возможных рисков использования искусственного интеллекта в высшем образовании. Интернет и платформы искусственного интеллекта обладают серьезным потенциалом для анализа различной информации - медицинских карт, лабораторных исследований, данных генома, выявления взаимосвязи заболеваний и социальных факторов. С помощью ИИ можно смоделировать виртуального пациента с различными патологиями, чтобы научить студентов навыкам диагностики и лечения. Однако есть опасения, что использование ИИ студентами может вызвать этические проблемы, связанные с конфиденциальностью пациентов, их информированным согласием на лечение и предвзятостью ИИ при принятии алгоритмических решений. Авторы акцентируют внимание на методе обучения студентов у постели больного как на наиболее эффективной модели обучения будущих врачей.
Ключевые слова: искусственный интеллект, высшее медицинское образование, цифровая трансформация, риски применения искусственного интеллекта в высшей школе, образовательные технологии, важность клинического опыта в медицинском образовании.
The field of higher education is influenced by the rapid development of artificial intelligence (AI) technologies. AI has great potential for higher education pedagogy, and its integration into the educational process should be aimed at improving the quality of education and preparing students for practical work, which is increasingly dependent on modern technologies [9].
We have prepared a descriptive review based on available literature research according to the experience and scientific views of the authors. The purpose of this review is to assess the positive aspects of the digitalization of higher education and the possible risks of using artificial intelligence in higher education.
AI opens up wide opportunities for individual learning - teaching a subject can be adapted to the style, speed and peculiarities of perception of each student. AI can track the student's progress, identify his strengths and weaknesses, allowing you to customize the educational material in order to develop the student's areas of knowledge in which help is needed at the moment [5]. Virtual simulation and AI-based training allow students to practice clinical skills in a realistic virtual environment to some extent, which is important for their future work with patients. [2,10] These technologies provide students with some hands-on experience without the potential ethical issues associated with working with real patients. Students around the world have long been able to participate in lectures, seminars, and case discussions remotely from anywhere, providing ongoing learning opportunities. Telemedicine platforms using AI for remote patient consultations allow students to gain some clinical experience working with patients under the guidance of clinicians.
There are many examples of how AI is used in medical education. AI is capable of quickly and in any volume analyzing various information - personal data of medical records, laboratory tests of patients, genome data, identifying links between diseases and family history and social factors, predicting the progression of the disease. With the help of AI, it is possible to simulate a virtual patient with various pathologies to teach students the skills of diagnosing and treating certain diseases. Using the capabilities of AI in the rapid processing of a huge array of scientific data, students can correctly plan scientific research and evaluate its results.
With the integration of artificial intelligence and digital tools in education, the role of the teacher is also changing. Teachers are becoming more coordinators and directors, focusing on personal support for students, emotional background and the creation of a positive learning environment. Professional development programs for teaching staff should equip teachers with the skills necessary to effectively use AI technologies in teaching practice. [5]
However, the integration of artificial intelligence into medical education in the 21st century brings both opportunities and new risks [8].
At the present stage of development of science, AI is far from omnipotent, and even more so in pedagogy, which is associated with human consciousness and medicine. There are legitimate concerns that the use of AI by students may raise ethical issues related to patient confidentiality, informed consent for treatment, and AI bias in algorithmic decision-making.
Making decisions about a sick or suffering person involves complex ethical and moral considerations that go beyond data analysis and algorithmic processing. Artificial intelligence systems clearly lack the ability to resolve these ethical dilemmas and uphold the values of dignity, compassion and respect for human life in the same way as doctors and other clinical staff.
AI-powered tools and applications often provide quick, automated solutions to problems, which can reduce students' desire to make decisions on their own. A student's excessive dependence on AI technologies may hinder the formation of an active position of a future doctor, while the role of the student's own opinion in decision-making is leveled out [3].
It is common knowledge that young people cannot take a step without a smartphone and the Internet. There is a danger of students becoming overly dependent on AI tools in the process of diagnosing and determining treatment tactics for patients. This creates risks for the development of sustainable clinical skills in students. Pedagogical science must develop a balance between the use of AI technologies and the preservation and development of students' cognitive abilities and professional ethical competencies. To achieve this, students should be fully encouraged to think critically about AI information by analyzing, evaluating, and synthesizing data from a variety of sources. Future doctors must learn to question assumptions, identify biases, and make judgments based on real data rather than relying solely on AI-generated information.
Despite the progress of AI, it is not capable of modeling live communication because the computer network does not have access to the perception of emotions and feelings. In a sense, neural networks in the educational process continue to act as a "quick reference" for the teacher and a simulator for the student. [3]. AI can have difficulty understanding the complex contextual factors associated with human illness or suffering. Human experience is often multifaceted and deeply individual, shaped by various social, cultural and psychological factors that are not easily quantified or interpreted by AI algorithms.
It is known that AI algorithms are based on the analysis of previous information, and if this data is limited or biased, AI generates inaccurate results. Students need to be made aware of these weaknesses of AI so that they understand the limitations of algorithmic data when working with AI models. AI algorithms in medical education must undergo rigorous quality assurance to ensure their accuracy, reliability, and representativeness [4].
Higher medical education has traditionally emphasized the development of critical thinking and analytical skills. However, with the vast amount of information available online and the ability of AI to process data instantly, students may rely on quick access to information rather than deep, critical analysis. Higher education pedagogy must adapt to ensure that students actively engage with content, challenge assumptions, and develop their analytical skills. Educators should critically evaluate educational resources and AI tools and educate students about the supporting role of AI in the diagnostic and treatment process.
The interpersonal aspect, humanistic communication between the patient and the doctor, is also very important in medical practice, which is crucial for trusting the doctor and helping the patient. If future doctors become overly dependent on AI and rely less on human interaction, this may negatively affect the development of strong interpersonal skills, empathy, and behavior at the bedside.
Medical education must adapt to learn the ethical use of AI in healthcare. Educators should explain to students in the classroom the importance of a balance between the use of technological advances and the preservation of humanistic values and empathy in future doctors.
Training future doctors at the bedside has been and remains the main way to prepare doctors since the time of Hippocrates [12]. Even in the age of information technology, it is necessary to remember that medicine is an applied science and without practice in the clinic, without students'
daily work with patients, it is impossible to prepare a modern doctor. In this sense, AI, unfortunately, will not significantly help the development of a future clinician. Theoretical knowledge obtained by students using modern information technologies without the ability to apply them at the patient's bedside is completely insufficient for the development of a modern doctor [1,11]. Higher education must adapt to new challenges and overcome the gap between traditional teaching methods and modern artificial intelligence tools in order to improve the quality of training specialists. A future doctor who successfully works with AI must transform from a passive consumer of knowledge into an active creator, capable of critical thinking, planning their independent work, taking initiative, formulating problems and finding solutions, including in nonstandard situations [6].
To summarize, although AI increases the chances of optimizing medical education, it does not replace the need for students to gain clinical experience at the patient's bedside and does not help to form the humanistic qualities and ethical standards of a future doctor. The cornerstone of pedagogy, the "student-mentor" relationship, remains unchanged, despite the progress of information technology.
Finding a balanced approach that combines AI with traditional pedagogical methods, emphasizing the strengths of each, will be important for preparing medical students to become knowledgeable, compassionate and ethical doctors of the XXI century.
REFERENCES
1. Байков А. Обучение у постели больного с точки зрения преподавателей, студентов и пациентов. Виртуальные технологии в медицине. 2022;(3):169-170. https://doi.org/10.46594/2687-0037_2022_3_1486;
2. Итинсон К.С. Инновационное обучение медицине на основе визуальных технологий Карельский научный журнал, № 1(30) стр. 16-18 29.02.2020
3. Лукичёв П.М., Чекмарев О.П. Риски применения искусственного интеллекта в системе высшего образования // Вопросы инновационной экономики. - 2024. - Том 14. - № 2. -doi: 10.18334/vinec.14.2.120731
4. Миндигулова А.А. Возможности и ограничения инструментов искусственного интеллекта в образовании / А.А. Миндигулова // Современное педагогическое образование. - 2022. - № 3. - С. 137-141.
5. Паскова А.А. Технологии искусственного интеллекта в персонализации электронного обучения. // Вестник Майкопского государственного технологического университета. 2019. Вып. 3(42). С. 113-122. DOI: 10.24411/ 2078-1024-2019-13010.
6. Щастный А.Т., Коневалова Н.Ю., Городецкая И.В., Кабанова С.А., Кугач В.В. Исследование формирования профессиональной компетентности студентов М 42 Медицинское образование XXI века: компетентностный подход и его реализация в системе непрерывного медицинского и фармацевтического образования / Сборник материалов Республиканской научно-практической конференции с международным участием. - Витебск: ВГМУ, 2017. - 653 с.
7. Boscardin CK, Gin B, Golde PB, Hauer KE. ChatGPT and Generative Artificial Intelligence for Medical Education: Potential Impact and Opportunity. Acad Med. 2024 Jan 1;99(1):22-27. doi: 10.1097/ACM.0000000000005439. Epub 2023 Aug 31. PMID: 37651677.
8. Knopp MI, Warm EJ, Weber D, Kelleher M, Kinnear B, Schumacher DJ, Santen SA, Mendon9a E, Turner L. AI-Enabled Medical Education: Threads of Change, Promising Futures, and Risky Realities Across Four Potential Future Worlds. JMIR Med Educ. 2023 Dec 25;9: e50373. doi: 10.2196/50373. PMID: 38145471; PMCID: PMC10786199.
9. Miao, Fengchun [author] [51], Holmes, Wayne [author] [18], Ronghuai Huang [author] [15], Hui Zhang [author] [6]Технологии искусственного интеллекта в образовании: перспективы и последствия Paris : UNESCO, 2022 ЮНЕСКО [68852] https://unesdoc.unesco.org/ark:/48223/pf0000382446
10. Nagi F, Salih R, Alzubaidi M, Shah H, Alam T, Shah Z, Househ M. Applications of Artificial Intelligence (AI) in Medical Education: A Scoping Review. Stud Health Technol Inform. 2023 Jun 29; 305:648-651. doi: 10.3233/SHTI230581. PMID: 37387115.
11. Pashkov, M.V., Pashkova, V.M. (2022). Problems and Risks of Digitalization in Higher Education. Vysshee obrazovanie v Rossii = Higher Education in Russia. Vol. 31, no. 3, pp. 4053, doi: 10.31992/0869-3617-2022-31-3-40-57
12. Peters M, Ten Cate O. Bedside teaching in medical education: a literature review. Perspect Med Educ. 2014 Apr;3(2):76-88. doi: 10.1007/s40037-013-0083-y. PMID: 24049043; PMCID: PMC3976479.
