Applications of Artificial Intelligence in Thalassemia: A Comprehensive Review
Author | Ferih, Khaled |
Author | Elsayed, Basel |
Author | Elshoeibi, Amgad M. |
Author | Elsabagh, Ahmed A. |
Author | Elhadary, Mohamed |
Author | Soliman, Ashraf |
Author | Abdalgayoom, Mohammed |
Author | Yassin, Mohamed |
Available date | 2023-06-18T11:22:32Z |
Publication Date | 2023-04-26 |
Publication Name | Diagnostics |
Identifier | http://dx.doi.org/10.3390/diagnostics13091551 |
Citation | Ferih, K., Elsayed, B., Elshoeibi, A. M., Elsabagh, A. A., Elhadary, M., Soliman, A., ... & Yassin, M. (2023). Applications of Artificial Intelligence in Thalassemia: A Comprehensive Review. Diagnostics, 13(9), 1551. |
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. |
Language | en |
Publisher | Multidisciplinary Digital Publishing Institute (MDPI) |
Subject | artificial intelligence B-thalassemia diagnosis iron deficiency anemia thalassemia |
Type | Article |
Issue Number | 9 |
Volume Number | 13 |
ESSN | 2075-4418 |
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