Published Paper Details:

The digital healthcare platform EPharma uses artificial intelligence together with machine learning capabilities to connect patients' symptoms detection to the generation of correct prescription recommendations. The Random Forest-based learning model in the system evaluates user symptoms to recommend medications effectively thus helping users avoid the dangerous implications of self-diagnosis and wrong self-treatment. EPharma uses strong authentication systems to guarantee safe user access between different user classes including patients and healthcare workers and pharmacists. The Flask framework creates the backend system and enables real-time data retrieval and maintains a MySQL database that operates with structured security parameters. The credibility of medical information in EPharma improves when users interact with external APIs such as Wikipedia and PubChem because this provides verified medication information along with their side effects and proper usage guidelines. Through its intuitive layout EPharma makes medical prescription tasks easy which lets healthcare reach more people with better operational efficiency. The system has built-in AI prediction technology which prevents medical mistakes and a security system using authentication protocols and encryption techniques protects confidential medical data.Through its medication management system EPharma assists healthcare providers with prescription automation which simultaneously decreases their workload while delivering better care outcomes to patients. Users of the platform can learn about their medication through educational resources which empower them with vital knowledge. The document explains how the system functions as well as describes installation methods and testing procedures while demonstrating its capabilities in modernizing healthcare operations. EPharma showcases how it changes digital healthcare by implementing intelligent automation with secure data handling in addition to improved user experiences while fixing current prescription system issues.