Using Fuzzy logic concepts in creating the decision making expert system for cardio — vascular diseases (CVD)

Duisenbayeva, A.; Atymtayeva, Lyazzat; Beisembetov, I. K.

doi:10.1109/icaict.2016.7991819

Cited by 9 publications

(2 citation statements)

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“…The system used seven main risk factors for heart stroke to identify the risk factors. In 2016, Duisenbayeva et al [55] demonstrated a more adaptable fuzzy inference system that aids doctors in making informed decisions regarding patients with coronary artery disease (CAD). CAD is one of the main causes of death worldwide.…”

Section: Review On Classification Identification and Detection Of Hea...mentioning

confidence: 99%

Review of Soft Computing Techniques in Monitoring Cardiovascular Disease in the Context of South Asian Countries

Thakur,

Sahu,

Swamy

et al. 2023

Applied Sciences

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The term “soft computing” refers to a system that can work with varying degrees of uncertainty and approximations in real-life complex problems using various techniques such as Fuzzy Logic, Artificial Neural Networks (ANN), Machine Learning (ML), and Genetic Algorithms (GA). Owing to the low-cost and high-performance digital processors today, the use of soft computing techniques has become more prevalent. The main focus of this paper is to study the use of soft computing in the prediction and diagnosis of heart diseases, which are considered one of the major causes of fatalities in modern-day humans. The heart is a major human organ that can be affected by various conditions such as high blood pressure, diabetes, and heart failure. The main cause of heart failure is the narrowing of the blood vessels due to excess cholesterol deposits in the coronary arteries. The objective of this study is to review and compare the various soft computing techniques that are used for the prediction, diagnosis, failure, detection, identification, and classification of heart disease. In this paper, a comprehensive list of recent soft computing techniques in heart condition monitoring is reviewed and compared with an experiment with specific applications to developing countries including South Asian countries. The relevant experimental outcomes demonstrate the benefits of soft computing in medical services with a high accuracy of 99.4% from Fuzzy Logic and Convolutional Neural Networks, with comparable results from other competing state-of-the-art soft computing models.

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Section: Review On Classification Identification and Detection Of Hea...mentioning

confidence: 99%

Review of Soft Computing Techniques in Monitoring Cardiovascular Disease in the Context of South Asian Countries

Thakur,

Sahu,

Swamy

et al. 2023

Applied Sciences

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“…The designed method was experimented on data sets from CCF and HIC, Budapest with an accuracy of 81.82%. Assemgul Duisenbayeva et al [12] revealed more adaptable and compatible fuzzy inference system (2016) that assist doctors and physicians in their decision-making for CAD disease. CP, BP, LDL CHL, BS, GR, MHR and AG were 7 input and 1 output variable having 5 features: sick (s1-s4), healthy.…”

Section: Review Of Research Papers From 2010-2013 Of Fl and Hybrid-based Approachesmentioning

confidence: 99%

Fuzzy Logic and Hybrid based Approaches for the Risk of Heart Disease Detection: State-of-the-Art Review

Kaur

Khehra²

2021

J. Inst. Eng. India Ser. B

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Artificial Intelligence, Machine Learning, Fuzzy Logic, Neural Network, Genetic Algorithm and their hybrid systems play vital role in the medical sciences to diagnose various diseases efficiently in the patients. The problems related to the heart are widely comon in today’s world. The risk of heart failure develops due to the narrowness and blockage in the coronary arteries of the heart as excess cholesterol deposits in the arteries and blood vessels that results in fatigue, chest pain, dyspnoea, sleeping difficulties and depression. This research aims to explore diverse work done on FL and Hybrid-based techniques to identify the risk of heart disease among the patients. The present study reveals publications along with the strength, operating system, accuracy rate and other specifications used in the identification of heart disease based on FL and Hybrid-based approaches since 2010. This survey contributes motivation for research scholars to generate more innovative ideas and continue their research work in the respective field. Moreover, the future model for direct service of the patients from old age homes to the Intensive Care Unit through ambulance services is also presented in this paper.

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Automated System for Monitoring of Educational Processes: Collection, Management, and Modeling of Data

Atymtayeva

Kozhakhmet

Savchenko

2020

Lecture Notes in Business Information Processing

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Using Fuzzy logic concepts in creating the decision making expert system for cardio — vascular diseases (CVD)

Cited by 9 publications

References 0 publications

Review of Soft Computing Techniques in Monitoring Cardiovascular Disease in the Context of South Asian Countries

Review of Soft Computing Techniques in Monitoring Cardiovascular Disease in the Context of South Asian Countries

Fuzzy Logic and Hybrid based Approaches for the Risk of Heart Disease Detection: State-of-the-Art Review

Automated System for Monitoring of Educational Processes: Collection, Management, and Modeling of Data

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