Atherosclerosis is a systemic disease that affects blood vessels in several basins. The patient often has multiple lesions in different sites – coronary arteries, brachiocephalic arteries, aorta, lower limb arteries. The prognosis and optimal treatment strategy are determined by the whole set of lesions, as well as their morphological features and individual progression rates, which can be assessed by the levels of various biomarkers.
Modern artificial intelligence and machine learning technologies make it possible to predict outcomes and complications, as well as the effectiveness of interventions, based on the analysis of large sets of heterogeneous medical data. The development and clinical testing of prognostic models provides new opportunities to determine the optimal strategy for comprehensive patient treatment, including minimally invasive or hybrid surgical procedures, medical therapy, screening and prevention of the most likely complications. To solve such problems, large sets of detailed and properly collected medical data are required.
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