Initial Release
In this workflow we are going to test the Vector Search functionality applied for the management of an hipotetic Master Patient Index using the Vector Storage capabilities of IRIS database.
Build the image we will use during the workshop:
$ git clone https://github.com/intersystems-ib/workshop-empi
$ cd workshop-empi
$ docker-compose build
The main purpose of this project is to develop an interoperability production to generate embeddings for the demographic information of patients received from HL7 messages and to provide possible duplicated patients as the Master Patient Index tools do using the vector search capabilities of IRIS.
This project is designed as a docker compose project developed on InterSystems IRIS for Health Community edition and it uses a pre-trained text-similarity model named all-MiniLM-L6-v2.
As we said before, our code is developed on InterSystems IRIS for Health leveraging the Embedded Python and Vector Search functionalities. The project is responsible for:
docker-compose up -d
Automatically an IRIS instance will be deployed and a production will be configured and run available to import data to create the prediction model and train it.
superuser
/ SYS
account.