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MEDICINE RECOGNITION AND CLASSIFICATION

Dr. Yasmeen Shaikh, Laxman Sanjay Patil, Sumit Malagoudanavar, Duradundi Rudragoudar, Sushantgouda Kempe

Abstract


The rapid growth of digital healthcare solutions has increased the demand for intelligent systems that support safe and informed use of medicines. Medicine recognition and classification play a critical role in preventing medication errors, especially in scenarios where users rely on self‑medication or lack immediate access to healthcare professionals. This paper presents a comprehensive Medicine Recognition and Classification system that identifies medicines using visual and descriptive attributes and categorizes them based on therapeutic purpose. The proposed system adopts a web‑based architecture integrated with artificial intelligence techniques to analyze medicine images, textual inputs, and symptom‑based information. By combining recognition, classification, and structured guidance within a single platform, the system aims to enhance medicine awareness, reduce misuse, and provide preliminary decision support while clearly maintaining medical safety boundaries. The results demonstrate that the system is effective, user‑friendly, and suitable for real‑world deployment as a supportive healthcare application.


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