Optimization assisted Kalman filter for cancer chemotherapy dosage estimation

Mohite, Utkarsha L.; Patel, Himanshu

doi:10.1016/j.artmed.2021.102152

Cited by 4 publications

(3 citation statements)

References 43 publications

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“…Usually, k Q as well as k R are constant matrixes, which are attained using the trial and error model. Nevertheless, definite problems have occurred in election process, and therefore for enhancement, a novel estimation of covariance matrix is proposed in [7] on the basis of the kernel-based error function. As a conservatory, a novel scaling factor is included with error function as used in [8].…”

Section: Covariance Matrix Estimationmentioning

confidence: 99%

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Shark Optimization Algorithm: Drug Dosage Estimation in Cancer Chemotherapy

Anbhazhagan¹

2022

JCMPS

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Chemotherapy is a medicine that is frequently exploited to treat cancer; the cancer cells widen as well as propagate more rapidly than the other cells in body. Although chemotherapy is a capable technique to analyze several types of cancers, treatment involves threat as it reasons side effects because of inappropriate drug practice. Thus, this research proposes a robust controller to control the dosage of the drug which is performed in parameter estimation. Additionally, a Modified Regularized Error Function (MREF)-Extended Kalman Filter (EKF) is adopted to approximate tumor cells as well as it can be used for different circumstances. In addition, the overfitting problem happens at the time of the drug dosage estimation which is resolved by exploiting this method. Furthermore, to improve the proposed model performance, the primary condition of EKF is fine-tuned using Shark Optimization Algorithm (SOA). Finally, the preeminence of the developed technique is revealed regarding the error analysis.

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Section: Covariance Matrix Estimationmentioning

confidence: 99%

“…Meanwhile, chemotherapy has both benefits as well as drawbacks. Still, if a patient is unsure regarding the starting diagnosis else reappearance, it is highly useful to go for chemotherapy [7]. One more notable feature of chemotherapy is the materialization of drug confrontation, generally seen in cancer patient's treatment.…”

Section: Introductionmentioning

confidence: 99%

Shark Optimization Algorithm: Drug Dosage Estimation in Cancer Chemotherapy

Anbhazhagan¹

2022

JCMPS

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“…The data used in the expert system can vary, such as images [2]- [4], signals [5], or medical record data which includes name, age, laboratory test results, and symptoms of the patient [6]- [8]. In the medical field, several expert systems have been developed, for example for estimating drug doses [6], [9], monitoring the disease progress [1], [2], [10], and detecting several types of diseases such as diabetes mellitus [11], pancreatic cancer [12], breast cancer [13], glaucoma [14], and dengue fever (DF) [15]- [17]. Dengue fever is an arboviral disease caused by infection with one of the four dengue virus serotypes.…”

Section: Introductionmentioning

confidence: 99%

Dengue classification method using support vector machines and cross-validation techniques

Hamdani

Hatta

Puspitasari

et al. 2022

IJ-AI

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Dengue is a dangerous disease that can lead to death if the diagnosis and treatment are inappropriate. The common symptoms that occur, including headache, muscle aches, fever, and rash. Dengue is a disease that causes endemics in several countries in South Asia and Southeast Asia. There are three varieties of dengue, such as dengue fever (DF), dengue hemorrhagic fever (DHF), and dengue shock syndrome (DSS). This disease can currently be classified using a machine learning approach with the input data being the dengue symptoms. This study aims to classify dengue types consisting of three classes: DF, DHF, and DSS using five classification methods including C.45, decision tree (DT), k-nearest neighbor (KNN), random forest (RF), and support vector machine (SVM). The dataset used consists of 21 attributes, which are the dengue symptoms. It was collected from 110 patients. The evaluation method was conducted using cross-validation with k-folds of 3, 5, and 10. The dengue classification method was evaluated using three parameters: precision, recall, and accuracy, which were most optimally achieved. The most optimal evaluation results were obtained using SVM with k-fold 3 and 10 with precision, recall, and accuracy values reaching 99.1%, 99.1%, and 99.1%, respectively.

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An observer-based adaptive fuzzy control for prescribing drug dosage in cancer treatment

Bandpey

Kalat

2022

Biocybernetics and Biomedical Engineering

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Optimization assisted Kalman filter for cancer chemotherapy dosage estimation

Cited by 4 publications

References 43 publications

Shark Optimization Algorithm: Drug Dosage Estimation in Cancer Chemotherapy

Shark Optimization Algorithm: Drug Dosage Estimation in Cancer Chemotherapy

Dengue classification method using support vector machines and cross-validation techniques

An observer-based adaptive fuzzy control for prescribing drug dosage in cancer treatment

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