基于非线性误差函数的癌症化疗剂量鲁棒控制器

IF 1.2 Q3 Computer Science Bio-Algorithms and Med-Systems Pub Date : 2020-09-28 DOI:10.1515/BAMS-2019-0056
U. L. Mohite, H. Patel
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引用次数: 2

摘要

摘要众所周知,化疗是治疗癌症等致死率最高的疾病的最重要的方法。如今,在整个治疗过程中,使用基于控制器的方法来寻找药物注射的最佳速率已经增加了很多。在这种情况下,本文建立了一种新的鲁棒控制器,该控制器随参数估计影响药物剂量。本文提出了一种新的基于非线性误差函数的改进比例因子扩展卡尔曼滤波器(NEF-EKF-ISF)。实际上,在传统的方案中,误差是使用传统的差分函数计算的,并将其用于EKF的更新过程。在我们之前的工作中,它已被转换为非线性误差函数。在这里,更新过程是基于先验误差函数的,尽管缩放到非线性环境。此外,本文还引入了一个考虑历史误差改进的比例因子,用于更新过程。最后,与其他传统方法相比,对所提出的控制器的性能进行了评估,这意味着药物剂量注射对正常细胞,免疫细胞和肿瘤细胞的适当影响。此外,观察到所提出的NEF-EKF-ISF能够以更好的准确率评估肿瘤细胞。
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Robust controller for cancer chemotherapy dosage using nonlinear kernel-based error function
Abstract It is well-known that chemotherapy is the most significant method on curing the most death-causing disease like cancer. These days, the use of controller-based approach for finding the optimal rate of drug injection throughout the treatment has increased a lot. Under these circumstances, this paper establishes a novel robust controller that influences the drug dosage along with parameter estimation. A new nonlinear error function-based extended Kalman filter (EKF) with improved scaling factor (NEF-EKF-ISF) is introduced in this research work. In fact, in the traditional schemes, the error is computed using the conventional difference function and it is deployed for the updating process of EKF. In our previous work, it has been converted to the nonlinear error function. Here, the updating process is based on the prior error function, though scaled to a nonlinear environment. In addition, a scaling factor is introduced here, which considers the historical error improvement, for the updating process. Finally, the performance of the proposed controller is evaluated over other traditional approaches, which implies the appropriate impact of drug dosage injection on normal, immune and tumor cells. Moreover, it is observed that the proposed NEF-EKF-ISF has the ability to evaluate the tumor cells with a better accuracy rate.
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来源期刊
Bio-Algorithms and Med-Systems
Bio-Algorithms and Med-Systems MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
3.80
自引率
0.00%
发文量
3
期刊介绍: The journal Bio-Algorithms and Med-Systems (BAMS), edited by the Jagiellonian University Medical College, provides a forum for the exchange of information in the interdisciplinary fields of computational methods applied in medicine, presenting new algorithms and databases that allows the progress in collaborations between medicine, informatics, physics, and biochemistry. Projects linking specialists representing these disciplines are welcome to be published in this Journal. Articles in BAMS are published in English. Topics Bioinformatics Systems biology Telemedicine E-Learning in Medicine Patient''s electronic record Image processing Medical databases.
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