GEMOGLOBIN MIQDORINI ANIQLASHNING ZAMONAVIY USULLARi VA ULARNING KAMCHILIKLARI

Abstract

This article reviews modern laboratory methods for measuring hemoglobin levels, outlining their advantages and limitations. It also discusses the future prospects of artificial intelligence (AI)-based diagnostic technologies.

Introduction: Hemoglobin (Hb) is an iron-containing protein located in red blood cells (erythrocytes) responsible for transporting oxygen from the lungs to tissues and removing carbon dioxide from the body. Changes in hemoglobin levels are crucial diagnostic indicators for anemia, polycythemia, hemoglobinopathies, and other hematological disorders.

Objective: 1.  To systematically review modern methods for hemoglobin measurement.

1. To assess the advantages and limitations of each method.


2. To evaluate the diagnostic potential of AI-based technologies.

Materials and Methods:  1. Spectrophotometric methods: Cyanmethemoglobin (HiCN) method — the international gold standard; requires toxic reagents (cyanide).

Laurell method — an immunochemical assay used to identify different hemoglobin variants.

1. Electrochemical methods: Biosensors (e.g., glucose oxidase-based) used in portable devices. These methods are fast but susceptible to interference.


2. Optical sensors: Near-Infrared Spectroscopy (NIRS) and Raman Spectroscopy — noninvasive methods; results may vary due to blood composition changes.


3. Capillary electrophoresis: Offers high-precision separation of hemoglobin fractions (e.g., HbA, HbS, HbF).


4. AI-based diagnostics: Smartphone apps and AI tools analyze skin or mucosal coloration to estimate hemoglobin. Promising but not yet fully standardized.

Results: However, the need for toxic reagents limits its applicability. Electrochemical and optical methods are portable but less precise. Capillary electrophoresis is especially effective in identifying hemoglobin variants. AI-based technologies show strong potential for future noninvasive diagnostics.

Conclusion: Each method has its strengths and weaknesses. The future lies in developing noninvasive, automated, and safe technologies. Method selection should be based on clinical context, technical availability, and required accuracy.