AN INTELLIGENT DRUG RECOMMENDATION FRAMEWORK USING PATIENT FEEDBACK AND REINFORCEMENT LEARNING

Abstract

In the current technology, everyone started taking suggestions from the machines. The advancement in technology has also evolved in medical industry. Most people are following drug recommendation systems. Traditional drug recommendation systems often rely only on a understands text and voice inputs from patients and recommends drugs based on their symptoms, while CNN models identify drugs from pill images. Reinforcement learning is then used to continuously improve the recommendations by learning from patient feedback and outcomes over time. Existing systems that use facial data do not ensure user privacy; however, our proposed system avoids using facial data, thereby providing better privacy protection.