meddle 0.1.0

Agentic Medical Deep Learning Engineer

Med-DLE: Agentic Medical Deep Learning Engineer

MedDLE is designed to be a codegen agentic system for medical deep learning tasks.

Quick Start

Setup environment

1. we recommand use conda to create a virtual environment:

conda create --name meddle python=3.11 
conda activate meddle

2. Then install meddle via:

pip install -r requirements.txt
pip install -e .

optional: use uv to speedup installation

pip install uv
uv pip install -r requirements.txt
uv pip install -e .

3. Get data from link and move the data into med_dl_tasks

4. remember to set up your private api key of OPENAI/ANTROPIC/OPENROUNTER

export OPENAI_BASE_URL="<your base url>" # (e.g. https://api.openai.com/v1)
export OPENAI_API_KEY="<your key>"

Basic codegen

Use bash run.sh to run the demo experiment.

MONAI-enhanced codegen

We highlight MONAI as a helpful candidate for medical DL codegen with Prompt/RAG mode:

Prompt mode

meddle data_dir="meddle/med_dl_tasks/odir5k_2d_mlc" exp_name="monai_prompt-odir5k_2d_mlc"\
     goal="Classify 2D Medical images into different categories in a multi-label setting" \
     eval="Use the average of kappa score, F-1 score, and AUC value metric between the predicted and ground-truth values." \
     agent.steps=20 agent.force_monai_with_prompt=true 

RAG mode

1. Create the knowledge database

Firstly, download the persisted database into meddle/monai_rag from link. Or you can create the db with this cmd:

cd meddle/monai_rag
python create_monai_rag_db.py

You could use python -m meddle.monai_rag.query_rag_db to check whether the creation succeeds.

2. enable the feature in agent

Here's some example:

meddle data_dir="meddle/med_dl_tasks/odir5k_2d_mlc" exp_name="monai_prompt_kb-odir5k_2d_mlc"\
     goal="Classify 2D Medical images into different categories in a multi-label setting" \
     eval="Use the average of kappa score, F-1 score, and AUC value metric between the predicted and ground-truth values." \
     agent.steps=20 agent.force_monai_with_prompt=false agent.enable_monai_knowledge_base=true

meddle data_dir="meddle/med_dl_tasks/odir5k_2d_mlc" exp_name="monai_prompt_kb_q2d-odir5k_2d_mlc"\
     goal="Classify 2D Medical images into different categories in a multi-label setting" \
     eval="Use the average of kappa score, F-1 score, and AUC value metric between the predicted and ground-truth values." \
     agent.steps=20 agent.force_monai_with_prompt=false agent.enable_monai_knowledge_base=true agent.enable_query2doc=true

🙏 Acknowledgement

• We thank all medical workers and dataset owners for making public datasets available to the community.
• Thanks to the open-source of the following projects, our code is developed based on their contributions:
  • aideml
  • monai