KATTA HAJMDAGI TIBBIY MA’LUMOTLARNI QAYTA ISHLASH ORQALI KASALLIKLARNI ERTA ANIQLASH USULLARI.
Kalit so‘zlar:
Katta hajmdagi ma’lumotlar, sun’iy intellekt, kasalliklarni erta aniqlash, mashinaviy o‘qitish, chuqur o‘qitish, tabiiy tilni qayta ishlash, tibbiy ma’lumotlar, ma’lumotlarni integratsiyalash, maxfiylik, onkologik kasalliklar, yurak-qon tomir kasalliklari, nevrologik kasalliklar, federativ o‘qitish, kvant hisoblash, elektron sog‘liqni saqlash yozuvlari, tibbiy tasvirlar, genomik ma’lumotlar, wearable qurilmalar.Abstrak
Zamonaviy tibbiyotda katta hajmdagi ma’lumotlar (Big Data) va sun’iy
intellekt texnologiyalari kasalliklarni erta aniqlashda muhim ahamiyatga ega bo‘lib bormoqda.
Ushbu maqola katta hajmdagi tibbiy ma’lumotlarni qayta ishlashning asosiy usullari, ularning
afzalliklari, qiyinchiliklari va kelajakdagi imkoniyatlarini atroflicha tahlil qiladi. Ma’lumotlarni
to‘plash, integratsiyalash, tozalash va tahlil qilish jarayonlari, shuningdek, mashinaviy o‘qitish,
chuqur o‘qitish va tabiiy tilni qayta ishlash kabi zamonaviy yondashuvlarning kasalliklarni
aniqlashdagi samaradorligi ko‘rib chiqiladi. Maqolada onkologik, yurak-qon tomir va nevrologik
kasalliklarning erta tashxisida ushbu texnologiyalarning qo‘llanilishi alohida yoritiladi. Shu bilan
birga, ma’lumotlar sifati, maxfiylik va resurslar bilan bog‘liq muammolar tahlil qilinadi.
Tadqiqotda ilg‘or texnologiyalar, xususan, federativ o‘qitish va kvant hisoblashning kelajakdagi
potensiali ta’kidlanadi. Maqola tibbiy ma’lumotlarni qayta ishlashning hozirgi holati va uning
sog‘liqni saqlash sohasidagi inqilobiy ta’sirini yoritishga qaratilgan bo‘lib, shifokorlar,
tadqiqotchilar va texnologlar uchun qimmatli ma’lumotlar taqdim etadi.
References
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
Rajkomar, A., Oren, E., Chen, K., Dai, A. M., Hajaj, N., Hardt, M., ... & Dean, J. (2018). Scalable and accurate deep learning with electronic health records. NPJ Digital Medicine, 1(1), 18. https://doi.org/10.1038/s41746-018-0029-1
Obermeyer, Z., & Emanuel, E. J. (2016). Predicting the future—big data, machine learning, and clinical medicine. New England Journal of Medicine, 375(13), 1216–1219. https://doi.org/10.1056/NEJMp1606181
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
Gulshan, V., Peng, L., Coram, M., Stumpe, M. C., Wu, D., Narayanaswamy, A., ... & Webster, D. R. (2016). Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs. JAMA, 316(22), 2402–2410.
https://doi.org/10.1001/jama.2016.17216
Hannun, A. Y., Rajpurkar, P., Haghpanahi, M., Tison, G. H., Bourn, C., Turakhia, M. P., & Ng, A. Y. (2019). Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network. Nature Medicine, 25(1), 65–69.
https://doi.org/10.1038/s41591-018-0268-3
Liu, Y., Jain, A., Eng, C., Way, D. H., Lee, K., Bui, P., ... & Coz, D. (2019). A deep learning system for differential diagnosis of skin diseases. Nature Medicine, 25(6), 900–908. https://doi.org/10.1038/s41591-019-0423-5
Beam, A. L., & Kohane, I. S. (2018). Big data and machine learning in health care. JAMA, 319(13), 1317–1318. https://doi.org/10.1001/jama.2017.18391
Raghupathi, W., & Raghupathi, V. (2014). Big data analytics in healthcare: Promise and potential. Health Information Science and Systems, 2(1), 3. https://doi.org/10.1186/2047-2501-2-3
McMahan, H. B., Moore, E., Ramage, D., Hampson, S., & Arcas, B. A. Y. (2017). Communication-efficient learning of deep networks from decentralized data. In Proceedings of the 20th International Conference on Artificial Intelligence and Statistics (pp. 1273–1282). PMLR. http://proceedings.mlr.press/v54/mcmahan17a.html
Downloads
Nashr qilingan
Nashr
Bo'lim
License
Copyright (c) 2025 A.Toxirov
This work is licensed under a Creative Commons Attribution 4.0 International License.
(+998)90 142-39-38
Andijon viloyati, Marhamat tumani, Qashqar ko’chasi 189-uy