Journal of cardiorespiratory research/Kardiorespirator tadqiqotlar jurnali Volume 5 Issue 3 (2024)
COMPARATIVE ASSESSMENT OF PREDICTING THE RISK OF CARDIOVASCULAR DISEASES IN PEOPLE WITH TYPE 2 DIABETES MELLITUS: INDICATORS, GEOGRAPHY, ARTIFICIAL INTELLIGENCE MODELS
Адылова Фатима Туйчиевна, Тригулова Раиса Хусаиновна, Давронов Рифкат Рахимович
Abstract
Type 2 diabetes mellitus (DM 2) is a common chronic disease caused by impaired insulin secretion. Due to complications of DM 2, the outcomes of this disease lead to severe cardiovascular diseases (CVD). Today, considering the constant increase in the number of patients with diabetes mellitus, it is necessary to find new tools to identify patients at high risk of cardiovascular complications. There are two key points in this process: a set of features and mathematical forecasting models. Therefore, the article provides answers to three questions:1. Is there a significant difference in the sets of features from different studies (purpose, geography, ethnicity)? 2. Is there a need to create your own feature sets rather than using well-known predictive indicators? 3. Is there an effect of using deep learning methods in comparison with traditional methods (statistics and machine learning)? The answers to these questions are based on the analysis of extensive recent publications on the problem under study.
сердечно-сосудистые заболевания, сахарный диабет, прогноз, машинное обучение, искусственный интеллектCardiovascular diseases, diabetes mellitus, prediction, machine learning, artificial intelligenceYurak-qon tomir kasalliklari, qandli diabet, asoratlari rivojlanishini, mashinali o'qitish, sun'iy intellekt
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