An AI-Driven Healthcare System for Early Disease Detection and Personalized Recommendation

Abstract

The integration of Artificial Intelligence (AI) and Machine Learning (ML) in healthcare has revolutionized early disease detection and personalized treatment strategies. This research presents an advanced healthcare system designed to enhance predictive diagnostics by efficiently managing medical records and analyzing laboratory reports. The system utilizes structured patient data to detect anomalies, assess health risks, and generate customized recommendations, including lifestyle changes, dietary plans, medication suggestions, and specialist referrals. Furthermore, AI-driven analytics facilitate data pattern recognition, assisting healthcare professionals in making informed decisions. The study focuses on optimizing database management, improving AI accuracy in disease risk assessment, and adhering to stringent healthcare data security standards. The system continuously evolves by incorporating real-time patient data, thereby shifting medical practices from reactive treatment to proactive care. By integrating AI-driven analytics, this research aims to improve diagnostic efficiency, reduce the workload on healthcare professionals, and enhance overall patient outcomes.