CREATING HIGH-ACCURACY PREDICTIVE MODELS BASED ON LARGE-SCALE MEDICAL DATA (ELECTRONIC HEALTH RECORDS, LABORATORY RESULTS, DIAGNOSTIC IMAGES)
Keywords:
Artificial Intelligence, Cardiovascular Diseases, Medical Diagnostics, Machine Learning, Deep Learning, Healthcare Technologies, Prediction, Clinical Decision Support, Digital Medicine, Electronic Health Records.Abstract
This research investigates the application of artificial intelligence (AI) technologies in predicting cardiovascular diseases, which remain a leading cause of mortality worldwide. The study emphasizes the importance of early diagnosis and personalized healthcare strategies in preventing severe complications. Using machine learning and deep learning algorithms, predictive models are developed based on large-scale medical data, including electronic health records, lab results, and diagnostic images. These AI-driven models demonstrate high accuracy, sensitivity, and specificity in identifying risk factors. The study also explores the integration of AI tools into clinical decision support systems, addressing data security, user-friendliness, and practical implementation challenges. The findings contribute to advancing digital medicine and support the effective adoption of AI in healthcare systems.
