THE ROLE AND IMPORTANCE OF ARTIFICIAL INTELLIGENCE IN THE DIAGNOSIS OF IRON DEFICIENCY ANEMIA IN CHILDREN (International journal of medical sciences, 2026)
Iron deficiency anemia (IDA) remains one of the most prevalent hematological disorders among children worldwide. Early diagnosis is essential to prevent developmental, cognitive, and immunological complications. In recent years, Artificial Intelligence (AI) technologies have demonstrated significant potential in improving diagnostic accuracy through automated analysis of laboratory and clinical data. This study evaluates the effectiveness of machine learning algorithms in detecting iron deficiency anemia in pediatric patients. The results indicate that AI-based models achieve diagnostic accuracy ranging from 85% to 95%, outperforming traditional manual assessment methods. The findings confirm that AI can significantly enhance early detection and clinical decision-making in pediatric anemia.