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AuthorFerih, Khaled
AuthorElsayed, Basel
AuthorElshoeibi, Amgad M.
AuthorElsabagh, Ahmed A.
AuthorElhadary, Mohamed
AuthorSoliman, Ashraf
AuthorAbdalgayoom, Mohammed
AuthorYassin, Mohamed
Available date2023-06-18T11:22:32Z
Publication Date2023-04-26
Publication NameDiagnostics
Identifierhttp://dx.doi.org/10.3390/diagnostics13091551
CitationFerih, 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.
URIhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85159180255&origin=inward
URIhttp://hdl.handle.net/10576/44516
AbstractThalassemia 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.
Languageen
PublisherMultidisciplinary Digital Publishing Institute (MDPI)
Subjectartificial intelligence
B-thalassemia
diagnosis
iron deficiency anemia
thalassemia
TitleApplications of Artificial Intelligence in Thalassemia: A Comprehensive Review
TypeArticle
Issue Number9
Volume Number13
ESSN2075-4418
dc.accessType Open Access


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