A Real-Time Classification System of Thalassemic Pathologies Based on Artificial Neural Networks

• Published in: Medical decision making Vol. 22; no. 1; pp. 18 - 26
• Main Authors: Amendolia, S. R., Brunetti, A., Carta, P., Cossu, G., Ganadu, M. L., Golosio, B., Mura, G. M., Pirastru, M. G.
• Format: Journal Article
• Language: English
• Published: Thousand Oaks, CA Sage Publications 2002; SAGE PUBLICATIONS, INC
• Subjects: Adolescent; alpha-Thalassemia - blood; alpha-Thalassemia - diagnosis; alpha-Thalassemia - pathology; beta-Thalassemia - blood; beta-Thalassemia - diagnosis; beta-Thalassemia - pathology; Decision Support Techniques; Erythrocyte Count; Erythrocyte Indices; Expert Systems; Female; Hematocrit; Hemoglobins - analysis; Humans; Male; Neural Networks (Computer); Sensitivity and Specificity; thalassemia; decision support; hemoglobinopathies; neural networks
• ISSN: 0272-989X; 1552-681X
• DOI: 10.1177/0272989X0202200102

Thalassemias are pathologies that derive from genetic defects of the globin genes. The most common defects among the population affect the genes that are involved in the synthesis of α and β chains. The main aspects of these pathologies are well explained from a biochemical and genetic point of view. The diagnosis is fundamentally based on hematologic and genetic tests. A genetic analysis is particularly important to determine the carriers of α-thalassemia, whose identification by means of the hematologic parameters is more difficult in comparison with heterozygotes for β-thalassemia. This work investigates the use of artificial neural networks (ANNs) for the classification of thalassemic pathologies using the hematologic parameters resulting from hemochromocytometric analysis only. Different combinations of ANNs are reported, which allow thalassemia carriers to be discriminated from normals with 94% classification accuracy, 92% sensitivity, and 95% specificity. On the basis of these results, an automated system that allows real-time support for diagnoses is proposed. The automated system interfaces a hemochromo analyzer to a simple PC.