RESUMO
Hemoglobin (Hb) abnormalities, such as thalassemia and structural Hb variants, are among the most prevalent inherited diseases and are associated with significant mortality and morbidity worldwide. However, there were not comprehensive reviews focusing on different clinical analytical techniques, research methods and artificial intelligence (AI) used in clinical screening and research on hemoglobinopathies. Hence the review offers a comprehensive summary of recent advancements and breakthroughs in the detection of aberrant Hbs, research methods and AI uses as well as the present restrictions anddifficulties in hemoglobinopathies. Recent advances in cation exchange high performance liquid chromatography (HPLC), capillary zone electrophoresis (CZE), isoelectric focusing (IEF), flow cytometry, mass spectrometry (MS) and polymerase chain reaction (PCR) etc have allowed for the definitive detection by using advanced AIand portable point of care tests (POCT) integrating with smartphone microscopic classification, machine learning (ML) model, complete blood counts (CBC), imaging-based method, speedy immunoassay, and electrochemical-, microfluidic- and sensing-related platforms. In addition, to confirm and validate unidentified and novel Hbs, highly specialized genetic based techniques like PCR, reverse transcribed (RT)-PCR, DNA microarray, sequencing of genomic DNA, and sequencing of RT-PCR amplified globin cDNA of the gene of interest have been used. Hence, adequate utilization and improvement of available diagnostic and screening technologies are important for the control and management of hemoglobinopathies.
