Fuzzy Logic System Implementation on the Performance Parameters of Health Data Management Frameworks

Vyas, Sonali; Gupta, Shaurya; Bhargava, Deepshikha; Boddu, Rajasekhar

doi:10.1155/2022/9382322

Cited by 13 publications

(8 citation statements)

References 30 publications

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“…This integration reduces the model’s uncertainty, improves its accuracy, and quantifies its uncertainty by examining the variance between the members’ predictions [ 70 ]. The limitation of ensemble methods is the increased computing power and time required for simultaneously testing different models [ 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 , 107 , 108 , 109 , 110 , 111 , 112 , 113 , 114 , 115 , 116 ].…”

Section: Digital Twins’ Methods For Dealing With Uncertaintiesmentioning

confidence: 99%

Using Constrained-Disorder Principle-Based Systems to Improve the Performance of Digital Twins in Biological Systems

Sigawi

Ilan

2023

Biomimetics

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Digital twins are computer programs that use real-world data to create simulations that predict the performance of processes, products, and systems. Digital twins may integrate artificial intelligence to improve their outputs. Models for dealing with uncertainties and noise are used to improve the accuracy of digital twins. Most currently used systems aim to reduce noise to improve their outputs. Nevertheless, biological systems are characterized by inherent variability, which is necessary for their proper function. The constrained-disorder principle defines living systems as having a disorder as part of their existence and proper operation while kept within dynamic boundaries. In the present paper, we review the role of noise in complex systems and its use in bioengineering. We describe the use of digital twins for medical applications and current methods for dealing with noise and uncertainties in modeling. The paper presents methods to improve the accuracy and effectiveness of digital twin systems by continuously implementing variability signatures while simultaneously reducing unwanted noise in their inputs and outputs. Accounting for the noisy internal and external environments of complex biological systems is necessary for the future design of improved, more accurate digital twins.

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Section: Digital Twins’ Methods For Dealing With Uncertaintiesmentioning

confidence: 99%

Using Constrained-Disorder Principle-Based Systems to Improve the Performance of Digital Twins in Biological Systems

Sigawi

Ilan

2023

Biomimetics

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“…Ensuring a user-friendly interface and gaining acceptability from patients, healthcare providers, and other stakeholders are essential components of user adoption. Security concerns require careful consideration, such as private key management and weaknesses in smart contracts [10]. Additional problems include the veracity of the data placed on the blockchain and the moral issues around patient rights and data ownership.…”

Section: Paper's Organizationmentioning

confidence: 99%

Securing Mobile Cloud-Based Electronic Health Records: A Blockchain-Powered Cryptographic Solution with Enhanced Privacy and Efficiency

Nauman,

Zhang,

et al. 2024

Journal of Intelligent Medicine and Healthcare

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The convergence of handheld devices and cloud-based computing has transformed how Electronic Health Records (EHRs) are stored in mobile cloud paradigms, offering benefits such as affordability, adaptability, and portability. However, it also introduces challenges regarding network security and data confidentiality, as it aims to exchange EHRs among mobile users while maintaining high levels of security. This study proposes an innovative blockchain-based solution to these issues and presents secure cloud storage for healthcare data. To provide enhanced cryptography, the proposed method combines an enhanced Blowfish encryption method with a new key generation technique called Elephant Herding Optimization with Resistance-Based Training (EHO-RBT). The implementation of blockchain-based solutions enhances privacy and authenticity by providing impermeable traces and ensuring validity. A comparative analysis reveals that the proposed method significantly outperforms the traditional cryptography simulations, with improved key generation times. The proposed method outperforms Rivest-Shamir-Adleman (RSA), Blowfish, advanced encryption standard (AES), elliptic-curve cryptography (ECC), whale optimization (WOA), elephant herding optimization (EHO), and moth-flame optimization (MFO) models by 51.04% to 92.64% for an average file size of about 10 kb. These results demonstrate the effectiveness and superiority of the proposed solution in terms of cryptography and key generation.

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“…ANFIS is a hybrid approach that combines ANN and fuzzy logic. ANFIS uses IF-THEN fuzzy rules (FRs) to describe the knowledge between a modeling problem's input and target datasets (10)(11)(12) . The block diagram of the ANFIS controller has presented in Figure 1.…”

Section: Adaptive Neuro-fuzzy Inference Systemmentioning

confidence: 99%

Improved Facial Identification Using Adaptive Neuro-Fuzzy Logic Inference System

Chandrasekhar¹,

Kumar²

2023

IJST

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Objectives: To suggest an efficient pose invariant face recognition system (PCA-ANFIS) based on PCA and ANFIS. Methods: Using a dual-tree complex wavelet transform technique, face image improvement is obtained. ORL and YALE B data sets are used in this process. To train and test the network to recognize the person, two sets of photos were used. The system will return recognized if the test image matches one of the image's training sets. The system will report not recognized if the test image does not match one of the image's training sets. Accuracy, specificity, sensitivity, precision, and recall are the criteria taken into account. The suggested approach is then evaluated and compared to other known, gold standard facial recognition algorithms, including PCA, WP&LDA, GOBER WAVELET, SVM, and Bayesian Classifier methods. Findings: The study results indicated that the image accuracy, specificity, sensitivity, precision, and recall are enhanced toa level of 90, 85, 95, 86, and 95 per cent respectively when compared with the test results of other known gold standard facial recognition algorithms viz., PCA, WP &LDA, GOBET WAVELET, SVM and Bayesian Classifier approaches by which it can be concluded that it is an efficient approach for facial identification. Novelty : Both the feature extraction strategy and the classification approach play a strong emphasis on these factors. Principal component analysis is used for feature extraction, while an Adaptive Neuro Fuzzy Inference System is used for classification. The study proposed a novel neuro-fuzzy system-based face recognition method that is proposed in this study correctly that identifies the input face photos with a higher recognition rate Compared to the existing reports.

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Fuzzy Logic System Implementation on the Performance Parameters of Health Data Management Frameworks

Cited by 13 publications

References 30 publications

Using Constrained-Disorder Principle-Based Systems to Improve the Performance of Digital Twins in Biological Systems

Using Constrained-Disorder Principle-Based Systems to Improve the Performance of Digital Twins in Biological Systems

Securing Mobile Cloud-Based Electronic Health Records: A Blockchain-Powered Cryptographic Solution with Enhanced Privacy and Efficiency

Improved Facial Identification Using Adaptive Neuro-Fuzzy Logic Inference System

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