Applications of Artificial Intelligence in Thalassemia: A Comprehensive Review

Author:

Ferih Khaled1ORCID,Elsayed Basel1ORCID,Elshoeibi Amgad M.1ORCID,Elsabagh Ahmed A.1ORCID,Elhadary Mohamed1ORCID,Soliman Ashraf2,Abdalgayoom Mohammed3,Yassin Mohamed13

Affiliation:

1. College of Medicine, QU Health, Qatar University, Doha P.O. Box 2713, Qatar

2. Hematology Section, Pediatrics Department, Hamad Medical Corporation (HMC), Doha P.O. Box 3050, Qatar

3. Hematology Section, Medical Oncology, National Center for Cancer Care and Research (NCCCR), Hamad Medical Corporation (HMC), Doha P.O. Box 3050, Qatar

Abstract

Thalassemia is an autosomal recessive genetic disorder that affects the beta or alpha subunits of the hemoglobin structure. Thalassemia is classified as a hypochromic microcytic anemia and a definitive diagnosis of thalassemia is made by genetic testing of the alpha and beta genes. Thalassemia carries similar features to the other diseases that lead to microcytic hypochromic anemia, particularly iron deficiency anemia (IDA). Therefore, distinguishing between thalassemia and other causes of microcytic anemia is important to help in the treatment of the patients. Different indices and algorithms are used based on the complete blood count (CBC) parameters to diagnose thalassemia. In this article, we review how effective artificial intelligence is in aiding in the diagnosis and classification of thalassemia.

Publisher

MDPI AG

Subject

Clinical Biochemistry

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