3D-BIOPRINTING TEXNOLOGIYASIDA DORI YUKLANGAN GIDROGELLARNI SUN'IY NEVRON TARMOQLARI (ANN) YORDAMIDA OPTIMALLASHTIRISH

Authors

  • Yusupova Karina O’razboyevna Sanoat farmatsiyasi fakulteti, sanoat farmatsiyasi yo‘nalishi 309-A guruh talabasi Author

Keywords:

3D-Bioprinting, Sun'iy neyron tarmoqlari, Reologiya, Sanoat farmatsiyasi.

Abstract

Tezisda personalizatsiyalangan dori shakllarini 3D-bioprinting usulida ishlab chiqarishda gidrogellarning reologik xususiyatlarini optimallashtirish o'rganilgan. Printer soplosidan gidrogelning aniq dozada chiqishini ta'minlash uchun sun'iy neyron tarmoqlari (ANN) algoritmlari qo'llanilgan. Optimallashtirilgan model 3D bosib chiqarish paytida dori dozasining aniqligini 99 foiz darajada ta'minlash imkonini berdi.

References

Bawa, P., et al. (2024). 3D-bioprinting of stimuli-responsive hydrogels. Biomaterials, 295, 115-128.

Maddikuri, R., et al. (2025). Application of artificial neural networks in pharmaceutical optimization. Advanced Drug Delivery Reviews, 185, 104-118.

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Published

2026-07-18

Issue

Vol. 5 No. 15 (2026): Applied Sciences in the Modern World

Section

Articles

How to Cite

Yusupova, K. (2026). 3D-BIOPRINTING TEXNOLOGIYASIDA DORI YUKLANGAN GIDROGELLARNI SUN’IY NEVRON TARMOQLARI (ANN) YORDAMIDA OPTIMALLASHTIRISH. Applied Sciences in the Modern World, 5(15), 51. https://www.in-academy.uz/index.php/ZDAF/article/view/54821
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