Machine Learning Algorithms for Predicting and Preventive Diagnosis of Cardiovascular Disease

Gulbakyt Sembina, Айгерим Айтим, Medet Shaizat

2022

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DOI 10.1109/sist54437.2022.9945708
Data confidence 70 medium
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Abstract

The article shows the creation of 6 trained models for the diagnosis of cardiovascular diseases based on 6 different machine learning algorithms. The best machine learning algorithm is determined. The quality of the model was assessed according to such metrics as the proportion of correct answers, accuracy, and recall. An overview of already implemented projects for the use of artificial intelligence in medicine in Kazakhstan and in the world is presented. Using data of 224 patients, is created training dataset to further train the models.