Application of Genetic Algorithm (GA) in Medical Science: A Review

Karmakar, Rahul

doi:10.1007/978-981-16-4641-6_8

Cited by 2 publications

(1 citation statement)

References 22 publications

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“…In the literature, genetic algorithm is preferred for solving many problems. Some of those; In solving the multi-mode multi-objective problem [18], it is used as a solution sequencing problem [18], in the solution of the effect maximization problem in social networks [19], in the solution of the dualobjective routing problem in dynamic networks [21], in the solution of the multi-objective reactive power distribution strategy problem for wind energy integrated systems [20], shape optimization [23], biomedicine [24]. Genetic algorithm is frequently preferred in the feature selection process, especially in recent years [26][27][28][29][30]…”

Section: Genetic Algorithmmentioning

confidence: 99%

Machine Learning-Based Comparative Study For Heart Disease Prediction

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2022

Advances in Artificial Intelligence Research

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Heart disease is one of the most common causes of death globally. In this study, machine learning algorithms and models widely used in the literature to predict heart disease have been extensively compared, and a hybrid feature selection based on genetic algorithm and tabu search methods have been developed. The proposed system consists of three components: (1) preprocess of datasets, (2) feature selection with genetic and tabu search algorithm, and (3) classification module. The models have been tested using different datasets, and detailed comparisons and analysis were presented. The experimental results show that the Random Forest algorithm is more successful than Adaboost, Bagging, Logitboost, and Support Vector machine using Cleveland and Statlog datasets.

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