| noteId | tags |
|---|---|
048efbb013c111ef9a5397c9c7cb3d4c |
FHIRspeak is a demonstration of a pipeline that implements a knowledge graph and vector semantic search on FHIR (Fast Healthcare Interoperability Resources) patient documents. The patient data is generated using Synthea, an open-source software that simulates patient histories. This rich, detailed data is ideal for testing healthcare software.
The ultimate goal of this pipeline is to enable AI-assisted searching through patient records. By transforming the patient data into a knowledge graph and using vector semantic search, we can make the search process more intelligent and context-aware. This can help healthcare professionals find the information they need more quickly and accurately, improving the efficiency and effectiveness of patient care.
Python 3.6 or higher is required to run the scripts in this repository.
To process the patient data, use the following command:
python flattenbundle.py --input "./Patients/*.json" --output ./Flatten_patients --subfolder
Please see license.txt.