Suppr超能文献

一种用于青光眼眼压调节和视神经损伤分数阶建模的量子启发式神经模糊滑模控制框架。

A quantum-inspired neural fuzzy sliding mode control framework for fractional-order modeling of intraocular pressure regulation and optic nerve damage in glaucoma.

作者信息

Amilo David

机构信息

Department of Mathematics, Near East University, Mersin 10, 99010, Nicosia, Cyprus.

Mathematics Research Center, Mersin 10, 99010, Nicosia, Cyprus.

出版信息

Sci Rep. 2025 Jul 2;15(1):23438. doi: 10.1038/s41598-025-99501-y.

Abstract

Glaucoma, a progressive neurodegenerative ocular disease, is primarily driven by elevated intraocular pressure (IOP), which results in optic nerve damage and irreversible vision loss. This study introduces a novel fractional-order mathematical model to capture the intricate dynamics of aqueous humor production, drainage, and the associated deterioration of the optic nerve in glaucoma. Building on this framework, this work proposes a Quantum-Inspired Neural Fuzzy Sliding Mode Control (QINF-SMC) framework, designed to address the nonlinear and time-varying nature of IOP regulation. The model highlights that persistent elevation in IOP leads to continuous optic nerve damage and disease progression, while impaired outflow resistance exacerbates glaucoma. Conversely, stable aqueous humor dynamics maintain normal IOP, preventing disease advancement. The proposed QINF-SMC framework integrates fractional-order calculus, fuzzy logic, and quantum-inspired optimization to achieve precise and adaptive control of IOP, mitigate optic nerve damage, and optimize aqueous humor dynamics. The framework achieves near-perfect 97.9% convergence, with excellent control stability and tightly regulated parameters, combining fast global optimization with precise refinement through advanced fractional-order dynamics. This approach offers a robust and innovative strategy for managing glaucoma, with potential implications for improving therapeutic outcomes and preserving vision.

摘要

青光眼是一种进行性神经退行性眼病,主要由眼内压(IOP)升高引起,IOP升高会导致视神经损伤和不可逆的视力丧失。本研究引入了一种新颖的分数阶数学模型,以捕捉青光眼患者房水生成、引流以及相关视神经退化的复杂动态过程。在此框架基础上,本研究提出了一种量子启发式神经模糊滑模控制(QINF-SMC)框架,旨在解决IOP调节的非线性和时变特性。该模型强调,IOP持续升高会导致视神经持续损伤和疾病进展,而流出阻力受损会加剧青光眼病情。相反,稳定的房水动态可维持正常的IOP,防止疾病进展。所提出的QINF-SMC框架整合了分数阶微积分、模糊逻辑和量子启发式优化,以实现对IOP的精确自适应控制,减轻视神经损伤,并优化房水动态。该框架实现了近97.9%的完美收敛,具有出色的控制稳定性和严格调控的参数,通过先进的分数阶动力学将快速全局优化与精确细化相结合。这种方法为青光眼管理提供了一种强大且创新的策略,对改善治疗效果和保护视力具有潜在意义。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验