Application of fuzzy logic and genetic algorithm in heart disease risk level prediction

Sharma, Purushottam; Saxena, Kanak

doi:10.1007/s13198-017-0578-8

Cited by 28 publications

(18 citation statements)

References 10 publications

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“…The combination of two or more than two technologies to find the solution of the peculiar problem, overcome the deficiency of one technique and strengthen the system are known as hybrid systems. In this study, hybridization of techniques has been described as, FL [ 8 , 9 , 11 , 12 , 14 , 15 , 19 , 20 , 25 – 32 , 35 , 36 , 38 – 41 , 45 , 48 , 50 , 52 , 53 ], GA [ 5 , 7 , 10 , 14 , 18 , 26 , 27 , 36 , 44 ], Artificial Neural Network (ANN) [ 5 , 7 , 10 , 13 , 35 , 42 – 44 , 51 ], Particle Swarm Optimization (PSO) [ 13 , 33 , 41 ], Ant Colony Optimization (ACO) [ 37 ], Naive Bayes (NB) [ 16 , 18 , 23 , 29 , 34 ], Decision Tree (DT) [ 8 , 18 , 20 , 22 , 23 , 28 , 41 , 48 , 51 ], K-means Clustering Algorithm [ 22 ], Logistic Regression (LR) [ 23 , 42 ], Multivariate Adaptive Regression Splines (MARS) [ 42 ], Rough Set (RS) [ 3 , 42 ], Support Vector Machine (SVM) [ 33 , 34 ], Random Forest (RF) [ 21 , 23 ], K-Nearest Neighbourhood (K-NN) […”

Section: Review Of Fl and Hybrid-based Approaches For The Risk Of Heart Disease Detectionmentioning

confidence: 99%

“…V.A medical center, CCF and LBF were data set sources. Coronary illness framework (2017) was applied by Purushottam Sharma et al [ 32 ] considered 13 input attributes: AG, GR, CP, FBS, RBP, RECG, THALACH, EXANG, OP, SLOPE, CA, THAL and CHOL from the data set of Hungary, Switzerland and U.S. The paper made use of very common combination of FL and GA, and brought 88.11% accuracy.…”

Section: Review Of Fl and Hybrid-based Approaches For The Risk Of Heart Disease Detectionmentioning

confidence: 99%

See 1 more Smart Citation

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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Section: Review Of Fl and Hybrid-based Approaches For The Risk Of Heart Disease Detectionmentioning

confidence: 99%

Section: Review Of Fl and Hybrid-based Approaches For The Risk Of Heart Disease Detectionmentioning

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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“…So, to minimize this it is necessary to analyze coronary disease. Coronary disease examination is usually in terms of signs, manifestations and physical examination of the patient [17]. For many people the first sign of heart dysfunction is a heart attack that occurs when the blood clot in the coronary arteries blocks the flow of blood into a part of the heart muscle [14].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy-based Decision for Coronary Heart Disease Diagnosis: Systematic Literature Review

Dianirani

Claudia

2021

EMACS Journal

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Coronary heart disease is usually caused by a buildup of fatty material and plaque inside the coronary arteries. The death rate caused by coronary heart diseases is threatening around the world. For the past two decades, most of the people from developing countries are suffering from heart disease. Diagnosing these diseases at earlier stages helps patients reduce the risk of death and also in reducing the cost of treatment. Decisions in medical diagnosis are mostly taken by expert’s experiences. In many cases, not all the expert’s experiences contribute towards effective diagnosis of a disease. Many alternative methods have been suggested for medical diagnosis in the healthcare domain. However, evaluating the functionality of coronary heart diseases diagnosis systems remains challenging. The purpose of this paper is to perform a study on literature related to fuzzy-based decision for diagnosis of coronary heart disease. Accordingly, the research gathered studies related to fuzzy-based decision for diagnosis of coronary heart disease between the periode 2016-2021.

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“…From this premise, it can be inferred that the diffuse logic to provide a solution needs a human know-how. Diffuse logic can consider variables of a qualitative nature that are hardly recognized by other techniques and provides an effective approach by systematizing the empirical terrain and transcribing and giving dynamism to experts' knowledge Sharma & Saxena, 2017).…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Logic in Business, Management and Accounting

Hernández¹,

Hidalgo²

2020

OJBM

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The aim of the paper is to show the implementation of fuzzy logic in business, administration and accounting, through the research published in Scopus. The results of the document focus on the following sections: 1) Fuzzy set theory, in business, administration and accounting. 2) Analysis of fuzzy logic bibliometrics in business, administration and accounting. 3) Identification and characterization of the documents or seminal documents most cited in applications of fuzzy logic in business, administration and accounting. The method used in this contribution is documentary research using the Scopus database and the VOSviewer science bibliometric analysis and mapping tool. In the future, this computational practice will focus on new diffuse models and the combination of these with other artificial intelligence techniques such as neural networks, genetic algorism, forage bacteria, among others.

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Application of fuzzy logic and genetic algorithm in heart disease risk level prediction

Cited by 28 publications

References 10 publications

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

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

Fuzzy-based Decision for Coronary Heart Disease Diagnosis: Systematic Literature Review

Fuzzy Logic in Business, Management and Accounting

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