An intelligent healthcare chatbot system designed to assist users with preliminary medical queries by analyzing symptoms and offering possible diagnoses. This AI-powered chatbot enhances healthcare accessibility, supports early disease detection, and delivers fast, accurate responses using advanced Natural Language Processing (NLP) and machine learning models.
This project was developed during an internship at Tata Steel Ltd., combining AI, NLP, and adaptive querying techniques to build a scalable, responsive, and reliable chatbot system. The goal is to create a user-friendly interface that enables quick medical assessments and reduces misdiagnosis through continuous feedback.
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🔍 Symptom-Based Diagnosis
Identify potential diseases by analyzing user-provided symptoms. -
🧠 NLP-Powered Conversations
Seamless, context-aware dialogue using Natural Language Processing. -
🗃️ SQL-Based Symptom Repository
Efficient query handling and fast data retrieval using relational databases. -
🔁 Adaptive Query Model
Improves accuracy over time by learning from user feedback. -
📈 Accuracy-Optimized AI Engine
Boosted diagnostic accuracy by 20% with machine learning models (TensorFlow).
- Language: Python
- Frameworks: Flask, TensorFlow
- Database: SQLite / MySQL
- Libraries: NLTK, Pandas, NumPy
- Implemented extensive test cases to ensure chatbot stability.
- Achieved:
- ✅ 20% improvement in diagnosis accuracy
- ✅ 25% faster symptom resolution
- ✅ 18% reduction in false positives through adaptive learning
This work was submitted for publication in IEEE SCOPES 2024
📄 “Integrating Intelligent Chatbots in Healthcare: AI-Based Healthcare Chatbot”
Presented at: 2nd International Conference on Signal Processing, Communication, Power, and Embedded Systems (SCOPES)
Co-sponsored by IEEE Kolkata Section.
IEEE Paper Link (once published)
Agniva Mukherjee
- B.Tech Electronics and Computer Engineering, SRM Institute
- 💼 AI Intern @ Tata Steel Ltd.
- 🔗 GitHub | LinkedIn
git clone https://github.com/agniva1803/medicalbot.git
cd medicalbot
pip install -r requirements.txt
python app.py