ARTIFICIAL INTELLIGENCE IN PEDIATRIC CARDIOLOGY: OPPORTUNITIES FOR EARLY DETECTION OF HEART DEFECTS

Abstract

Congenital heart defects in pediatric cardiology are one of the main causes of death and disability in children. Early detection of these defects increases the effectiveness of treatment and prevents complications. In recent years, the introduction of artificial intelligence (AI) technologies into medicine has brought diagnostic processes to a new level. This article discusses the application of artificial intelligence in pediatric cardiology, in particular, the possibilities of early detection of heart defects based on electrocardiography, echocardiography and imaging diagnostics. It is proven that algorithms based on artificial intelligence help doctors make a quick, accurate and objective diagnosis. Congenital heart defects are one of the pathologies that are widespread among children and can lead to severe clinical consequences. The article analyzes the classification of TYN, morphological forms (for example: interventricular septal defect, atrial septal defect, tetralogy of Fallot, etc.), their etiology and pathogenesis. Clinical signs, early diagnosis methods (ECG, echocardiography, pulse oximetry, prenatal diagnosis), and modern treatment approaches will also be reviewed