{"title":"基于非线性误差函数的癌症化疗剂量鲁棒控制器","authors":"U. L. Mohite, H. Patel","doi":"10.1515/BAMS-2019-0056","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":42620,"journal":{"name":"Bio-Algorithms and Med-Systems","volume":"16 1","pages":""},"PeriodicalIF":1.2000,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/BAMS-2019-0056","citationCount":"2","resultStr":"{\"title\":\"Robust controller for cancer chemotherapy dosage using nonlinear kernel-based error function\",\"authors\":\"U. L. Mohite, H. Patel\",\"doi\":\"10.1515/BAMS-2019-0056\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":42620,\"journal\":{\"name\":\"Bio-Algorithms and Med-Systems\",\"volume\":\"16 1\",\"pages\":\"\"},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2020-09-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1515/BAMS-2019-0056\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Bio-Algorithms and Med-Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1515/BAMS-2019-0056\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bio-Algorithms and Med-Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/BAMS-2019-0056","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Computer Science","Score":null,"Total":0}
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.
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.