TIBBIYOT SOHASIDA SUN'IY INTELLEKTNING O'RNI
Ключевые слова:
Kalit so‘zlar: Sun'iy intellekt (AI), tibbiyot, diagnostika, kasalliklarni aniqlash, sog‘liqni saqlash tizimi, ma'lumot tahlili, mashinani o‘rganish, tibbiy ma'lumotlar, davolash innovatsiyalari, shifokor yordamchi texnologiyalar, AI va etika, rivojlanish istiqbollari.Аннотация
Annotatsiya: Tibbiyotda Sun’iy Intellektning O‘rni mazkur maqolada tibbiyot sohasida sun’iy intellektning (AI) roli va ahamiyati o‘rganiladi. Sun’iy intellektning diagnostika jarayonini tezlashtirish, kasalliklarni aniqlashda aniqlikni oshirish, va davolash jarayonlarini individuallashtirishdagi yutuqlari ko‘rsatib o‘tiladi. Shuningdek, AI yordamida katta hajmdagi tibbiy ma’lumotlarni tahlil qilish orqali sog‘liqni saqlash tizimlarini takomillashtirish misollari keltiriladi. Annotatsiya sun’iy intellektning hozirgi holati, imkoniyatlari va kelajakdagi rivojlanish istiqbollarini qisqacha yoritib, bu texnologiyaning afzalliklari va yuzaga kelishi mumkin bo‘lgan cheklovlariga ham e’tibor qaratadi.
Библиографические ссылки
1. Topol, E. (2019). Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again. Basic Books.
2. Obermeyer, Z., Powers, B. W., 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
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. Wang, F., Casalino, L. P., & Khullar, D. (2020). "Deep Learning in Medicine – Promise, Progress, and Perils," JAMA Internal Medicine, 180(10), 1347-1349. https://doi.org/10.1001/jama.2020.6795
5. Challen, R., Denny, J., Pitt, M., Gompels, L., & Edwards, T. (2019). "Artificial Intelligence, Bias and Clinical Safety," BMJ Quality & Safety, 28(3), 231-237. https://doi.org/10.1136/bmjqs-2018-008117
6. Rajpurkar, P., Irvin, J., Zhu, K., Yang, B., Mehta, H., Duan, T., & Ding, D. (2017). "Deep Learning for Chest Radiograph Diagnosis – A Retrospective Comparison of the CheXNeXt Algorithm to Radiologists," PLOS Medicine, 14(11), e1002386. https://doi.org/10.1371/journal.pmed.1002386
