Phentrieve

Phentrieve is an advanced AI-powered system for mapping clinical text to Human Phenotype Ontology (HPO) terms using a Retrieval-Augmented Generation (RAG) approach. It supports multiple languages and offers robust tools for benchmarking, text processing, and HPO term retrieval.

For comprehensive documentation, please visit the Phentrieve Documentation Site.

Key Features

• Multilingual HPO term mapping using state-of-the-art embedding models
• Advanced text processing pipeline including semantic chunking and assertion detection
• Extensive benchmarking framework for model evaluation and comparison
• User-friendly interfaces: CLI, FastAPI backend, and Vue.js frontend
• Support for cross-encoder re-ranking to improve retrieval precision

Benchmark Results

Performance on 570 German clinical terms (BioLORD-2023-M model):

Retrieval Mode	MRR	Hit@1	Hit@10	Ont Sim@1
Single-vector	0.695	55.8%	94.0%	79.9%
Multi-vector (all_max)	0.892	84.0%	97.4%	91.9%

+28% MRR improvement with multi-vector retrieval using label, synonym, and definition embeddings.

Quick Start

Install Phentrieve using pip:

pip install phentrieve

For detailed setup and usage instructions, including Docker deployment, please see our Getting Started Guide.

Basic Usage

# Launch interactive query mode
phentrieve query --interactive

# Process clinical text to extract HPO terms
phentrieve text process "The patient exhibits microcephaly and frequent seizures."

Discover more commands and options in the User Guide.

Docker Deployment

Deploy Phentrieve using Docker Compose for production environments:

# Linux: Setup volume permissions (required)
sudo ./scripts/setup-docker-volumes.sh

# macOS/Windows: No setup needed, skip to next step

# Start services
docker-compose up -d

# Access the application
# - API: http://localhost:8000
# - Frontend: http://localhost:8080

For detailed deployment instructions, security best practices, and troubleshooting, see the Docker Deployment Guide.

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