230 -5 (79) 2025 - Jumayev F.E. - THE ROLE OF ARTIFICIAL INTELLIGENCE IN MODERN MEDICINE

THE ROLE OF ARTIFICIAL INTELLIGENCE IN MODERN MEDICINE

Jumayev F.E. - Bukhara State Medical Institute named after Abu Ali ibn Sina

Resume

Artificial Intelligence (AI) is rapidly transforming modern medicine by enhancing diagnostics, treatment planning, and patient care. Through machine learning and data analysis, AI systems can detect diseases, interpret medical images, support clinical decisions, and even assist in robotic surgeries. These technologies offer faster, more accurate, and cost-effective healthcare solutions. However, the rise of AI also presents ethical, legal, and practical challenges, including data privacy concerns and algorithmic bias. This paper explores the current applications, benefits, limitations, and future potential of AI in medicine. By integrating AI responsibly, healthcare systems can improve outcomes, increase access, and support medical professionals in delivering personalized and efficient care.

Keywords: Artificial Intelligence (AI); Machine Learning; Deep Learning; Medical Diagnostics; Healthcare Technology; AI in Surgery; Predictive Analytics; Virtual Health Assistants; Personalized Medicine; Medical Data Analysis.

First page

1142

Last page

1145

For citation:Jumayev F.E. - THE ROLE OF ARTIFICIAL INTELLIGENCE IN MODERN MEDICINE//New Day in Medicine 5(79)2025 1142-1145 https://newdayworldmedicine.com/en/new_day_medicine/5-79-2025

List of References

  1. Esteva, A., Robicquet, A., Ramsundar, B., Kuleshov, V., DePristo, M., Chou, K., ... Dean, J. (2019). A guide to deep learning in healthcare. Nature Medicine, 25(1), 24-29. https://doi.org/10.1038/s41591-018-0316-z
  2. Topol, E. J. (2019). High-performance medicine: the convergence of human and artificial intelligence. Nature Medicine, 25(1), 44-56. https://doi.org/10.1038/s41591-018-0300-7
  3. Rajkomar, A., Dean, J., Kohane, I. (2019). Machine learning in medicine. New England Journal of Medicine, 380(14), 1347-1358. https://doi.org/10.1056/NEJMra1814259
  4. Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S., ... 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
  5. Jumayev F.E. - The role and prospects of artificial intelligence in perinatal medicine // New Day in Medicine 4(78)2025 1072-1075 https://newdayworldmedicine.com/en/new_day_medicine/4-78-2025.
  6. Ting, D. S. W., et al. Deep learning in ophthalmology: The technical and clinical considerations. Progress in Retinal and Eye Research, 2019.
  7. Goodfellow, I., Bengio, Y., Courville, A. Deep learning. MIT Press, 2016.
  8. Ф. Э, Жумаев, and Мухамедова Ш. Т. 2024. “Перинатальное Поражение Мозга: Патогенетические Аспекты И Информативность Биохимических Маркеров”. Research Journal of Trauma and Disability Studies 3 (2):349-52. https://journals.academiczone.net/index.php/rjtds/article/view/2201.
  9. Эркинбекович, Д. Ф. (2024). Последствия перинатального повреждения нервной системы - патогенез и клиника гипоксически-ишемической энцефалопатии. scientific journal of applied and medical sciences, 3(1), 101–103. Retrieved from https://sciencebox.uz/index.php/amaltibbiyot/article/view/9348
  10. Эркинович, Д. Ф. (2023). Нервно-Мышечная Диагностика У Детей. Research Journal of Trauma and Disability Studies, 2(11), 223–229. Retrieved from https://journals.academiczone.net/index.php/rjtds/article/view/1485

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