- Traditional medicine websites can be complex, hindering user understanding. Our solution introduces a chat-based platform for a more user-friendly experience.
- Patients often have many questions about medicines and obtaining timely answers can be a lengthy process. Our project provides real-time guidance through an AI-powered chatbot.
- Incorrectly taking dosages or medications is dangerous and critical. This chatbot can offer guidance, minimizing the risk of inappropriate usage.
- Illegible doctor prescriptions create confusion among patients. A handwriting model can recognize the doctor's prescription and take orders accordingly.
- Certain medications may have adverse interactions, presenting health risks. By using the user's purchase history, the chatbot prevents complications by offering personalized recommendations.
- User Interface Module: Web Interface: HTML5, Css3, JavaScript
- Input Processing Module: NLP: Python (NLTK, spaCy, Transformers library), Machine Learning: Python (scikit-learn, TensorFlow, PyTorch)
- Medicine Database Module: Database: MySQL, Backend: Node.js, Python (Django)
- Stock Management Module: Database: MySQL, Backend: Node.js, Python (Django)
- Order Processing Module: Backend: Node.js, Python (Django)
- LLM Module
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Efficient Prescription Processing: The chatbot extracts releevant information from text and images, and reduces the time and effort required to do them manually. It minimizes aerorrs and ensures accurate dosage.
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User Profile: User can check their previous orders and can request help from customer care.
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Secondary Consultant: The chatbot can provide personalized guidance on past interactions and demographic data of user.
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Effortless Order Placement: The chatbot proceses payments and estimates delivery times. It simplifies the ordering process, making it convenient for users while reducing workload.
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Ease Of Management: The various backend tools allow for easy management of the database by administrators.