KASALLIKNI BIRLAMCHI DIAGNOSTIKASINING NEYRON TARMOQLARGA ASOSLANGAN USULLARI

Authors

  • Boliyeva Dilrabo Nurbek qizi

Keywords:

Kalit so'zlar: EKG,RNN,NLP,LSTM,sun'iy neyron,diagnostika,tashxis,sun'iy intellect,akson,sigmoid funksiya.

Abstract

Annotatsiya: Sun'iy neyron tarmoqlari yuqori aniqlik bilan tashxis qo'yishi mumkin va eng muhimi, bunday texnologiya asosiy tashxis yoki kuzatuvni aniqlash uchun ishlatilishi mumkin. Ushbu maqolada bemorlar birlamchi o'z-o'zini tashxislash uchun sun'iy neyron tarmoqlarga asoslangan usul yordamida algoritm va dastur yaratish masalasi qaraladi.

References

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Esteva, A., et al. Dermatologist-level classification of skin cancer with deep neural networks. Nature, 2017. 542(7639), 115-118.

Coudray, N., et al. Classification and mutation prediction from non-small cell lung cancer histopathology images using deep learning. Nature Medicine, 2018. 24(10), 1559-1567.

Attia, Z. I., et al. An artificial intelligence-enabled ECG algorithm for the identification of patients with atrial fibrillation during sinus rhythm: a retrospective analysis of outcome prediction. The Lancet, 2019. 394(10201), 861-867.

Haenssle, H. A., et al. Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists. Annals of Oncology, 2018. 29(8), 1836-1842.

Published

2023-10-10

How to Cite

Boliyeva Dilrabo Nurbek qizi. (2023). KASALLIKNI BIRLAMCHI DIAGNOSTIKASINING NEYRON TARMOQLARGA ASOSLANGAN USULLARI. Journal of New Century Innovations, 38(1), 160–168. Retrieved from https://newjournal.org/new/article/view/8966