Revolutionizing Thalassaemia Detection: The Emerging Role of Artificial Intelligence and Machine Learning
DOI:
https://doi.org/10.65406/2.2/4-16/2025Keywords:
Thalassaemia, iron deficiency anaemia, artificial intelligence, machine learning, β globin chainAbstract
Thalassaemia is a serious anaemia disease caused by genes, which results in serious health and economic problems in the entire globe, particularly in those areas with restricted access to health care. Thalassaemia and iron deficiency anemia are clinically similar as they have similar hematological characteristics. Conventional diagnostic tools comprising of molecular test, conventional index and complete blood count (CBC) parameters may provide pertinent information but are not always available, are not affordable and take a long turnaround time. Over the last few decades, the field of medicine diagnostics has encountered a disruptive technology in the form of Artificial Intelligence (AI) since it is both cheap and quick and incredibly precise in treatment. The artificial intelligence (AI) like Decision Tree, Support Vector Machine, and Neural Networks can be able to determine the traits of thalassaemia using the normal hematological data. Additional methods to be proven to be more dependable in diagnosis, like deep learning and sophisticated algorithms, like XGBoost and Convolutional Neural Networks (CNN) can be further tested to introduce additional reliability in a diagnosis. It has also been found in comparative studies that AI-based models tend to be more sensitive and specific than standard indices, this is the reason that these technologies are currently being utilized as genetic counseling and screening tools. Nevertheless, problems of data quality, bias of the model, and considerations of ethics persist. Nevertheless, AI can serve as an important supportive resource in the early diagnosis, accurate differentiation, and better management of thalassaemia in low resource healthcare facilities despite the challenges. The combination of AI and molecular testing is bright in terms of global thalassaemia control and individualized medication.
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