HYBRID ARTIFICIAL INTELLIGENCE-BASED ALGORITHM DESIGN FOR CARDIOVASCULAR DISEASE DETECTION

نویسندگان

چکیده

Objective: Cardiovascular Disease (CVD) is a disease that negatively affects the blood vessel system due to plaque formation as result of accumulation on inner wall vessels. In diagnostic phase, angiography results are evaluated by physicians. New algorithms based artificial intelligence, including new technologies, needed for diagnosing CVD time-consuming and high cost methods. Materials Methods: The heart dataset available open-source sharing site Kaggle was used in study. includes 14 clinical findings. study, after features were selected with Fischer feature selection algorithm, they classified Ensemble Decision Trees (EDT), k-Nearest Neighborhood Algorithm (kNN), Neural Networks (NN). A hybrid intelligence algorithm also created using three Results: According classification results, EDT %96.19, kNN %100, NN %86.17, determined %99.3 success rate. Conclusion: obtained it proposed diagnosis can be practice

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ژورنال

عنوان ژورنال: Advances in artificial intelligence research

سال: 2022

ISSN: ['2757-7422']

DOI: https://doi.org/10.54569/aair.1141465