Концептуальные основы фундаментальных, прикладных и инновационных исследований в трансформации педагогического образования и воспитания

Mazkur “Pedagogik ta’lim va tarbiya transformatsiyasida fundamental, amaliy va innovatsion tadqiqotlarning konseptual asoslari” mavzusidagi Xalqaro ilmiy-amaliy konferensiya Oliy ta’lim, fan va innovatsiyalar vazirligining 2026-yil 16-yanvardagi 11-sonli buyrug'i bilan 2026-yilda xalqaro va respublika miqyosida o‘tkaziladigan ilmiy va ilmiy-texnik tadbirlar rejasiga kiritilgan bo'lib, 2026-yil 23-iyun kuni Namangan davlat pedagogika instituti Ilmiy tadqiqotlar, innovatsiyalar va ilmiy-pedagogik kadrlar tayyorlash bo'limi tomonidan o'tkazilgan.

1+ Выпуски
228+ Статьи
260+ Участники
English

THE GROWING IMPORTANCE OF ARTIFICIAL INTELLIGENCE IN MODERN MEDICINE

Дата публикации
23.06.2026
Журнал
Концептуальные основы фундаментальных, прикладных и инновационных исследований в трансформации педагогического образования и воспитания
Выпуск
Сборник материалов международной научно-практической конференции на тему: «Концептуальные основы фундаментальных, прикладных и инновационных исследований в трансформации педагогического образования и воспитания»
Страницы
623-627
DOI
10.5281/zenodo.21200968

Авторы

Аннотация

Artificial Intelligence (AI) is rapidly transforming the field of medicine by improving diagnostic accuracy, enhancing patient care, and accelerating medical research. This article examines the major roles of AI in healthcare, including disease detection, medical imaging, patient monitoring, clinical decision support, and drug development. It further explores the integration of AI with telemedicine, robotic surgery, and personalized medicine, while addressing the ethical, legal, and technical challenges that accompany its implementation. The study concludes that, despite existing limitations, AI possesses substantial potential to revolutionize healthcare systems and improve global health outcomes when integrated responsibly alongside human clinical expertise.

Ключевые слова

Diagnosis Drug Development Healthcare Medical Imaging Patient Care Technology

Список литературы

1. World Health Organization (WHO). (2021). Ethics and Governance of Artificial Intelligence for Health: WHO Guidance. Geneva: World Health Organization.
2. Topol, E. (2019). Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again. New York: Basic Books.
3. Esteva, A., Kuprel, B., Novoa, R. A., Ko, J., Swetter, S. M., Blau, H. M., & Thrun, S. (2017). Dermatologist-level classification of skin cancer with deep neural networks. Nature, 542(7639), 115–118. https://doi.org/10.1038/nature21056
4. Rajpurkar, P., Irvin, J., Zhu, K., Yang, B., Mehta, H., Duan, T., Ding, D., Bagul, A., Langlotz, C., Shpanskaya, K., Lungren, M. P., & Ng, A. Y. (2017). CheXNet: Radiologist-level pneumonia detection on chest X-rays with deep learning. arXiv preprint arXiv:1711.05225.
5. Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S., Wang, Y., Dong, Q., Shen, H., & Wang, Y. (2017). Artificial intelligence in healthcare: Past, present and future. Stroke and Vascular Neurology, 2(4), 230–243. https://doi.org/10.1136/svn-2017-000101
6. Davenport, T., & Kalakota, R. (2019). The potential for artificial intelligence in healthcare. Future Healthcare Journal, 6(2), 94–98. https://doi.org/10.7861/futurehosp.6-2-94
7. Yu, K.-H., Beam, A. L., & Kohane, I. S. (2018). Artificial intelligence in healthcare. Nature Biomedical Engineering, 2(10), 719–731. https://doi.org/10.1038/s41551-018-0305-z
8. Litjens, G., Kooi, T., Bejnordi, B. E., Setio, A. A. A., Ciompi, F., Ghafoorian, M., van der Laak, J. A. W. M., van Ginneken, B., & Sánchez, C. I. (2017). A survey on deep learning in medical image analysis. Medical Image Analysis, 42, 60–88. https://doi.org/10.1016/j.media.2017.07.005
9. Vamathevan, J., Clark, D., Czodrowski, P., Dunham, I., Ferran, E., Lee, G., Li, B., Madabhushi, A., Shah, P., Spitzer, M., & Zhao, S. (2019). Applications of machine learning in drug discovery and development. Nature Reviews Drug Discovery, 18(6), 463–477. https://doi.org/10.1038/s41573-019-0024-5
10. Obermeyer, Z., Powers, B., Vogeli, C., & Mullainathan, S. (2019). Dissecting racial bias in an algorithm used to manage the health of populations. Science, 366(6464), 447–453. https://doi.org/10.1126/science.aax2342
11. U.S. Food and Drug Administration. (2023). Artificial Intelligence and Machine Learning in Software as a Medical Device. Center for Devices and Radiological Health, Digital Health Center of Excellence. https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-and-machine-learning-software-medical-device