SUN’IY INTELLEKT ASOSIDA TASHXISLASH TIZIMINING TUZILISHI
Authors
Keywords: genetic profile, biometric information, normalization of values, deep learning, convolutional neural network, recurrent neural networks, machine learning algorithms, Feature Selection and Extraction
Abstract
References
1. Esteva A., Kuprel B., Novoa R. A., Ko, J., Swetter S. M., Blau, H. M., & Thrun S. Dermatologist-level classification of skin cancer with deep neural networks. Nature, 542(7639), 2017. –Р. 115–118.
2. Rajpurkar P., Irvin, J., Zhu, K., Yang, B., Mehta, H., Duan, T., ... & Lungren M.P. 2017. CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning. arXiv preprint arXiv:1711.05225.
3. Aytmuratov B.Sh., Nurimov P.B., Yesbergenov H.S., Analysis of X-Ray images using artificial intelligence algorithms for medical diagnostics, Science and Education in Karakalpakstan. 2024 № 2/2 ISSN 2181-9203.
4. Nurimov P.B, Yesbergenov H.S, Tibbiyotda sun’iy intellekt texnologiyalarini qo‘llash, Raqamli texnologiyalarning iqtisodiyot va ta’limdagi o‘rni mavzusidagi xalqaro ilmiy-amaliy anjumani ma’ruzalar to‘plami I tom, Muhammad al-Xorazmiy nomidagi Toshkent axborot texnologiyalari universiteti Samarqand filiali, 316-324-b. 2024.
5. Rivera S.C, Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension, Nature Medicine, Vol. 26, -P. 1351-1363. 2020.
6. Litjens G., Kooi, T., Bejnordi, B. E., Setio, A. A.,. A survey on deep learning in medical image analysis. Medical Image Analysis, 2017. –Р. 42, 60-88.
7. Topol E.J. High-performance medicine: the convergence of human and artificial intelligence. Nature Medicine, 25(1), 2019.