You will get Personal Healthcare AI Agent
Project details
Transform Healthcare with AI-Powered Vietnamese Medical Assistant
# You can see the demo on github: QDung210/Personal-Healthcare-AI-Agent
I'm offering a production-ready Healthcare AI Agent - a rare specialization that sets this project apart.
What Makes This Unique:
✅ Fine-Tuned Vietnamese Medical Models - Custom embedding model achieving 87.4% accuracy on ViHealthQA benchmarks, outperforming major competitors
✅ Advanced RAG System - Retrieval-Augmented Generation ensures accurate, source-backed medical information
✅ Multi-Modal Capabilities - Text chat + X-ray image classification (14 lung diseases) + PDF document processing
✅ Production-Grade Architecture - FastAPI backend, TypeScript frontend, Docker deployment, AWS Bedrock integration
Core Features:
Real-time medical Q&A
Intelligent appointment scheduling via conversational AI
X-ray disease classification
PDF document upload & OCR for medical records
Brave Search integration for expanded knowledge
Qdrant vector database for semantic search
Tech Stack: Pydantic-AI, AWS Bedrock, Fine-tuned Qwen-7B (305M params), TensorFlow, Docker, TypeScript
⚡ Delivered with full source code, documentation, and deployment support.
# You can see the demo on github: QDung210/Personal-Healthcare-AI-Agent
I'm offering a production-ready Healthcare AI Agent - a rare specialization that sets this project apart.
What Makes This Unique:
✅ Fine-Tuned Vietnamese Medical Models - Custom embedding model achieving 87.4% accuracy on ViHealthQA benchmarks, outperforming major competitors
✅ Advanced RAG System - Retrieval-Augmented Generation ensures accurate, source-backed medical information
✅ Multi-Modal Capabilities - Text chat + X-ray image classification (14 lung diseases) + PDF document processing
✅ Production-Grade Architecture - FastAPI backend, TypeScript frontend, Docker deployment, AWS Bedrock integration
Core Features:
Real-time medical Q&A
Intelligent appointment scheduling via conversational AI
X-ray disease classification
PDF document upload & OCR for medical records
Brave Search integration for expanded knowledge
Qdrant vector database for semantic search
Tech Stack: Pydantic-AI, AWS Bedrock, Fine-tuned Qwen-7B (305M params), TensorFlow, Docker, TypeScript
⚡ Delivered with full source code, documentation, and deployment support.
AI Algorithms
Large Language Model, Multimodal Large Language Model, Transformer ModelAI Applications
AI Chatbot, Image Processing, Natural Language Generation, Natural Language UnderstandingAI Development Language
PythonAI Tools
Hugging Face, Word2vecAI Models
BERT, ChatGPT, LLaMAWhat's included
| Service Tiers |
Starter
$20
|
Standard
$30
|
Advanced
$50
|
|---|---|---|---|
| Delivery Time | 14 days | 21 days | 30 days |
Number of Revisions | 2 | 1 | 5 |
AI Model Integration | |||
Batch Normalization | - | - | |
Database Integration | |||
Detailed Code Comments | |||
Image Upscaling | - | - | |
MLOps | - | - | |
Model Deployment | - | ||
Model Documentation | - | ||
Model Monitoring | - | - | |
Model Testing & Optimization | - | ||
Model Tuning | - | - | |
Natural Language Processing | |||
NLP Tokenization | - | ||
Pre-Training | - | - | |
Prompt Engineering | - | ||
Setup File | |||
Source Code |
Optional add-ons
You can add these on the next page.
AWS Bedrock Setup & Configuration
(+ 5 Days)
+$20
Additional Language Support
(+ 5 Days)
+$50Frequently asked questions
About Dung
AI & Machine Learning | Backend APIs, Chatbots
Hanoi, Vietnam - 3:18 pm local time
CAREER OBJECTIVE
Aspiring AI Engineer currently studying
Artificial Intelligence , with a
strong interest in DevOps and MLOps.
Seeking a role to gain practical
experience in deploying and monitoring
AI systems in production environments
Steps for completing your project
After purchasing the project, send requirements so Dung can start the project.
Delivery time starts when Dung receives requirements from you.
Dung works on your project following the steps below.
Revisions may occur after the delivery date.
Project Setup & Requirements Analysis
Discovery & Planning Description: Review requirements, set up development environment, configure AWS Bedrock, create project architecture documentation, and establish communication channels.
Backend Development
AI Agent & API Implementation Description: Develop FastAPI backend, integrate fine-tuned models (Qwen-7B, Vietnamese embeddings), implement RAG system with Qdrant, set up Brave Search integration, and create appointment booking logic.