Key points are not available for this paper at this time.
Modern medicine is increasingly focused on a personalized approach to diagnosis and treatment. This approach is based on a thorough analysis of biomarkers — objective indicators reflecting various aspects of health. Unleashing the potential of biomarkers requires tools that can effectively process and interpret large volumes of data. In this context, artificial intelligence (AI) technologies are becoming increasingly popular. AI systems have unique capabilities for identifying and interpreting complex relationships between biomarkers. Examples of using AI to predict cardiovascular diseases and oncology based on biomarker data are given. AI is capable of not only finding correlations, but also studying cause-and-effect relationships, which opens new horizons in understanding the pathogenesis of diseases. AI also opens up opportunities for personalizing therapeutic interventions based on the analysis of individual patient characteristics.
A. P. Krylov (Sat,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: