MediLens: An AI-Powered Medicine Information and Assistance System
Abstract
Medication errors and difficulty accessing reliable
drug information remain significant challenges in modern healthcare.
MediLens is an AI-powered web-based medicine information
and assistance system designed to provide accurate,
accessible, and easy-to-understand medication details for users.
The system integrates Optical Character Recognition (OCR) to
identify medicines from images of drug labels or packaging and
retrieves verified information from trusted biomedical databases.
Natural Language Processing (NLP) and a cloud-based Large
Language Model (LLM) are used to generate contextual summaries
and answer user queries through an interactive conversational
assistant. The backend is implemented using the FastAPI
framework and communicates with external knowledge sources
and AI services through secure API integration. MediLens follows
a modular architecture that includes OCR processing, information
retrieval, and AI-driven response generation to ensure
scalability and reliability. Core functionalities include medicine
identification from images, structured drug information retrieval,
automated summarization, and interactive question answering.
By combining retrieval-based verification with conversational
AI, MediLens aims to improve public health literacy, reduce
misinformation about medications, and demonstrate the practical
application of artificial intelligence in healthcare information
systems.
Keywords:
Artificial Intelligence, Healthcare Informatics, Large Language Models, Medicine Information System, FastAPIPublished
Issue
Section
License
Copyright (c) 2026 International Journal on Emerging Research Areas

This work is licensed under a Creative Commons Attribution 4.0 International License.
All published work in this journal is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
How to Cite
Similar Articles
- R Karthika, Maria Toms, S R Aadrash, P U Prabath, InsightAI: Bridging Natural Language and Data Analytics , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Arya Raj S, R Gopika Krishnan, Drishya Das, Rohith R, Jocelyn Ann Joseph, Personality Profiling Using CV Analysis , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Leon B. Samuel, Amrutha Solomon, Enterprise-Grade Test Case Generation Framework Combining Retrieval-Augmented Generation with Multi-Modal Requirement Analysis , International Journal on Emerging Research Areas: Vol. 6 No. 1 (2026): IJERA
- Liyan Grace Shaji, Ayana Soman, Diya V Varghese, Elizabeth Anna Liju, Ethel Jimmy, A Comprehensive Survey on Automated Radiology Report Generation: Methods, Explainability, Multimodal Alignment, and Clinical Integration , International Journal on Emerging Research Areas: Vol. 6 No. 1 (2026): IJERA
- Felix Jobi, Nagaraj Menon K S, Revathy Biju, Shraya S Santhosh, StockGenie: AI-Driven Stock Market Assistant and Forecasting System , International Journal on Emerging Research Areas: Vol. 6 No. 1 (2026): IJERA
- Krishnendu B, Sreelakshmi A, Sumayya Maheen, Zameel Hassan, Honey Joseph, Chatbot-Enabled Symptom Assessment: Revolutionizing Disease Diagnosis and Patient Care , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Amrutha Priya C B, Nitha C Velayudhan, Arjun K S, Aleena Francis, Divya P S, AI Enabled Robot for Data Collection in Unreachable and Extreme Environment , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Maria Sajeeve, Karthik Vinod, Kausalya Sumesh, Joby Jose, Minu Cherian, KALO:AI-Powered Precision in Nutrition Tracking , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Febin Cheriyan, Deni Tom Jacob, Joanna Daniel, Haby S Mathews, Honey Joseph, Pneumonia Detection From Chest X-Rays Using Deep Learning : A Comprehensive Review , International Journal on Emerging Research Areas: Vol. 6 No. 1 (2026): IJERA
- Alan K George, Arpita Mary Mathew, Asin Mary Jacob, Elizabeth Antony, Shiney Thomas, Lung Cancer Subtype Classification Using Deep Learning Models , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
You may also start an advanced similarity search for this article.
