AI based Differentiation of Beta-Thalassemia and Iron Deficiency Anemia.

  • Authors

    • Aravinda Kandadai
    • Prof. Ashok Shigli
    • Dr. Shaik Ayeesha Begam
    2018-11-26
    https://doi.org/10.14419/ijet.v7i4.29.21637
  • Artificial intelligence, Beta-thalassemia, Iron deficiency anemia, Support Vector machine.

  • Abstract

    Thalassemia is a genetic disorder that leads to variation in the protein structure of the hemoglobin molecule, which causes profound anemia that kills untreated affected children before the age of 3 years. Unfortunately, the traditional RBC indices based methods do not distinguish between β-thalassemia and a normal iron deficiency anemia, causing wrong treatment to be administered. Techniques such as HPLC, serum ferritin analysis and molecular studies are needed to help differentiate them. The main drawbacks of these techniques are that, it takes a long time to issue the results, it is expensive and is not available everywhere. Here, we attempt to use a heuristic algorithm as well as AI based techniques to accurately predict the occurrence of thalassemia from the easily available RBC data itself. The AI technique is based on support vector machine. An accuracy of 60 % and 96% are obtained for the heuristic algorithm and the AI technique respectively. Details of this work are presented in this paper.

     

  • References

    1. [1] Epidemiology of β-thalassemia in Western India: mapping the frequencies and mutations in sub-regions of Maharashtra and Gujarat Roshan Colah, Ajit Gorakshakar, Supriya Phanasgaonkar, Edna D’Souza, Anita Nadkarni, Reema Surve, Pratibha Sawant, Dilip Master, Ramesh Patel, Kanjaksha Ghosh, Dipika Mohanty, British Journal of Haematology; Volume 149, Issue 5, pages 739–747, June 2010

      [2] Ehsani MA, Shahghol E, Rahiminejad MS, et al. A new index for discrimination between iron deficiency anemia and beta-thalassemia minor: results in 284 patients. Pak J Biol Sci.2009;12:473-475

      [3] Wang Z., Xue X. (2014) Multi-Class Support Vector Machine. In: Ma Y., Guo G. (eds) Support Vector Machines Applications. Springer, Cham

  • Downloads

  • How to Cite

    Kandadai, A., Ashok Shigli, P., & Shaik Ayeesha Begam, D. (2018). AI based Differentiation of Beta-Thalassemia and Iron Deficiency Anemia. International Journal of Engineering & Technology, 7(3.29), 674-676. https://doi.org/10.14419/ijet.v7i4.29.21637

    Received date: 2018-11-26

    Accepted date: 2018-11-26

    Published date: 2018-11-26