Received 29.01.2024, Revised 26.04.2024, Accepted 30.05.2024

Expert systems for analysis of biomedical information in the diagnosis of acute leukemia

Jinqiong Li, Sergii Pavlov, Oleksii Stakhov

This study contributes to further improvement of knowledge and accuracy of diagnostic methods. It also plays an important role in the diagnosis and treatment of acute leukemia today. The application of various technologies, exchange of experience and ideas have significant achievements that will have a revolutionary effect in patient care and improve diagnostic accuracy. The most significant contribution is the development and implementation of technologies, especially artificial intelligence (AI) or machine learning. The study illustrates how AI-based models can help evaluate and interpret biomedical data, providing more accurate diagnoses and facilitating decision-making. Trained on large databases, such models show promise in identifying subtle patterns indicative of different subtypes of leukemia, which could lead to more precise and tailored treatments. The study of new biomarkers, the use of advanced imaging techniques, and the use of new technologies such as blockchain for data security represent promising avenues for progress. However, addressing challenges such as regulatory compliance, ethical considerations, and the complexity of identifying appropriate drug candidates remains key to responsible development

acute leukemia, diagnosis and therapy, biomedical image, images of blast and non-blast blood cells
157-164
Li, J., Pavlov, S., & Stakhov, O. (2024). Expert systems for analysis of biomedical information in the diagnosis of acute leukemia. Information Technologies and Computer Engineering, 21(1), 157-164. https://doi.org/10.31649/1999-9941-2024-59-1-157-164

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