AI-based prediction of flow dynamics of blood blended with gold and maghemite nanoparticles in an electromagnetic microchannel under abruptly changes in pressure gradient.

IF 1.5 4区 生物学 Q3 BIOLOGY
Electromagnetic Biology and Medicine Pub Date : 2025-01-01 Epub Date: 2025-05-13 DOI:10.1080/15368378.2025.2501733
Poly Karmakar, Sukanya Das, Sanatan Das
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引用次数: 0

Abstract

In cardiovascular research, electromagnetic fields (EMFs) induced by Riga plates are applied to study and potentially manipulate blood flow dynamics, offering insights for therapies against arterial plaque deposition and for understanding varied blood flow behaviors. This research focuses on predicting the flow patterns of blood infused with gold and maghemite nanoparticles (gold-maghemite/blood) inside an EM microchannel under these electromagnetic influences and abruptly change in pressure gradient. The study models these flows by considering radiation heat emission and Darcy drag forces within porous media. Mathematical representation involves time-variant partial differential equations, resolved through Laplace transform (LT) to yield compact-form expressions for the model variables. The outcomes, including shear stress (SS) and rate of heat transfer (RHT) across the microchannel, are analyzed and displayed graphically, highlighting the effects of modified Hartmann number and electrode width on these parameters. Hybrid nano-blood (HNB) and nano-blood (NB) exhibit distinct thermal characteristics, with HNB transferring more heat within the blood flow. These study implements a cutting-edge AI-powered approach for high-fidelity evaluation of critical flow parameters, achieving unprecedented prediction accuracy. Validation results confirm the algorithm's excellence, with SS predictions reaching 99.552% (testing) and 97.019% (cross-validation) accuracy, while RHT predictions show 100% testing accuracy and 97.987% cross-validation reliability. This convergence of nanotechnology with advanced machine learning paves the way for transformative clinical applications that could redefine standards of care in surgical oncology, interventional cardiology, and therapeutic radiology. This model underpins potential applications such as controlled drug release and magnetic fluid hyperthermia, enhancing procedures like cardiopulmonary bypass, vascular surgery, and diagnostic imaging.

基于人工智能的磁赤铁矿和金纳米颗粒混合血液在压力梯度突变条件下在电磁微通道中的流动动力学预测。
在心血管研究中,Riga板诱导的电磁场(emf)被应用于研究和潜在的操纵血流动力学,为治疗动脉斑块沉积和理解不同的血流行为提供了见解。这项研究的重点是预测在电磁影响和压力梯度突然变化的情况下,注入金和磁赤铁矿纳米颗粒(金-磁赤铁矿/血液)的血液在EM微通道内的流动模式。该研究通过考虑多孔介质中的辐射热辐射和达西阻力来模拟这些流动。数学表示涉及时变偏微分方程,通过拉普拉斯变换(LT)求解得到模型变量的紧凑形式表达式。结果,包括剪切应力(SS)和热传递率(RHT)通过微通道进行了分析和图形化显示,突出了修改哈特曼数和电极宽度对这些参数的影响。混合纳米血(HNB)和纳米血(NB)表现出明显的热特性,HNB在血流中传递更多的热量。这项研究采用了一种尖端的人工智能方法,对关键流动参数进行高保真度评估,实现了前所未有的预测精度。验证结果证实了算法的卓越性,SS预测准确率达到99.552%(测试)和97.019%(交叉验证),RHT预测准确率为100%,交叉验证信度为97.987%。纳米技术与先进机器学习的融合为变革性临床应用铺平了道路,可以重新定义外科肿瘤学、介入心脏病学和治疗放射学的护理标准。该模型支持诸如控制药物释放和磁流体热疗等潜在应用,增强心肺循环,血管手术和诊断成像等程序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.60
自引率
11.80%
发文量
33
审稿时长
>12 weeks
期刊介绍: Aims & Scope: Electromagnetic Biology and Medicine, publishes peer-reviewed research articles on the biological effects and medical applications of non-ionizing electromagnetic fields (from extremely-low frequency to radiofrequency). Topic examples include in vitro and in vivo studies, epidemiological investigation, mechanism and mode of interaction between non-ionizing electromagnetic fields and biological systems. In addition to publishing original articles, the journal also publishes meeting summaries and reports, and reviews on selected topics.
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