The potential of artificial intelligence (AI) regarding anemia diagnosis and management

Anemia stands out as the most prevalent blood disorder globally. Various factors can contribute to its development, including insufficient production of red blood cells (RBCs) as well as degradation of RBCs. The functional impairment of RBCs in anemia can result in a wide spectrum of symptoms, ranging from fatigue and weakness to severe, life-threatening conditions. The primary method for detecting anemia is the commonly employed complete blood count (CBC) test. However, for certain cases and to distinguish between different types of anemia, more advanced tests become necessary. Artificial intelligence (AI) has emerged as a technology designed to replicate human intelligence and perform tasks that typically require human cognitive abilities. AI models possess the capability to comprehend patterns and associations, enabling them to recognize and analyze images. In the context of anemia, studies have demonstrated that AI algorithms can analyze images of various physical characteristics such as conjunctiva, palm, tongue, and fingernails. By estimating hemoglobin concentration, these algorithms can predict the presence of anemia. Furthermore, AI systems have also exhibited the ability to analyze clinical data, including laboratory tests and blood smears, to predict anemia and identify specific types. It is worth noting that previous studies in the context if AI applications in anemia have been conducted on relatively small populations. However, the accuracy achieved in these investigations has been satisfactory, suggesting that AI systems could potentially play a significant role in the future of anemia diagnosis and management.