A Lightweight AI-Powered Doctors Assistant for Unified Healthcare Data Management and Analytics

The digital transformation of healthcare has accelerated in recent years, yet significant challenges remain in integrating medical data, ensuring real-time analytics, and providing effective decision support for clinicians. Conventional hospital information systems (HIS) often operate in silos, leading to inefficiencies, delays, and reduced quality of care. This work presents CareTrack, an AI-powered doctor’s assistant and patient management platform designed to integrate multiple healthcare functions into a single lightweight solution. The system includes electronic patient record management, appointment scheduling, analytics dashboards, machine learning-based risk stratification, and conversational chatbot interfaces. Built on a Flask backend, SQLite storage, and modular web frontend, CareTrack is designed for scalability, IoT integration, and cloud readiness. Experimental evaluation using a dataset of 100 patients demonstrates improved performance over baseline HIS, including reduced latency in record retrieval, higher classification accuracy, and better usability for clinicians.