AI-ENHANCED INTEGRATION OF MULTIMODAL DATA FOR EARLY PREDICTION OF HEART FAILURE EXACERBATIONS IN HIGH-RISK GROUPS

Abstract

Healthcare professionals consider advanced cardiovascular medicine to represent a major advancement because artificial intelligence enables correct diagnosis of hypertensive heart disease.  This research investigates the application of artificial intelligence systems and machine learning methods throughout various stages of hypertensive heart disease evaluations until treatment stages and patient prognostic evaluations.  Through the combination of machine learning with deep learning systems healthcare professionals achieve excellent diagnostics through individual treatment planning and disease prediction abilities.  People use AI based mobile tools with wearable technology to track their vital signs in real-time thus speeding up hypertension detection.  The application of AI-systems contains multiple issues about data privacy and algorithm transparency that coincide with requirements for quality data while demonstrating substantial disruptive qualities.  Previous research documents serve as a foundation to demonstrate how AI supports hypertensive heart disease management but also identifies the challenges and advantages in addition to requiring better research strategies for medical AI optimization.