User bio

I'm a Technical Graduate at InterSystems, working in the Developer Relations team.

In a past life, I did a PhD doing Electron Microscopy of biological molecules. I enjoy making things, often with code.

Edinburgh
Member since Sep 10
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When I tested this morning, the FHIR Management part was available in the FHIR namespace before the 

do ##class(HS.Util.Installer.Foundation).Install("fhir")

process even finished running, so I don't think it should take any time for changes to propagate. I'm afraid I can't help further, it sounds like a frustrating issue but glad it seems to have resolved itself today. 

Hi Robert, they should be available! I just checked with a fresh install and I can access them, but before doing so you need to create a FHIR enabled namespace. Here's the steps I took: 

Do a fresh install with docker: 

# Fresh docker install
docker run --name iris-for-health --publish 32782:1972 --publish 32783:52773 -d intersystems/irishealth-community:latest-em 

# Start IRIS terminal

docker exec -it iris-for-health iris session iris

Then install a new namespace using HS.Util.Installer.Foundation (I called it FHIR)

set $NAMESPACE = "%SYS"

do:'##class(%SYS.Namespace).Exists("fhir") ##class(HS.Util.Installer.Foundation).Install("fhir")

 With just this step, I can open the FHIR Server Configuration by going to the health tab of the management portal: 

Click FHIR: 

Then click FHIR Server Management to get to the FHIR Server UI with all the available features on the left hand panel:

I hope this helps! If not, you can also try using a docker-compose template here: pjamiesointersystems/Dockerfhir: Open repository for training with FHIR using IRIS for Health Community Edition

You can still install the InterSystems AutoML onto the normal IRIS Community edition with a pip install - its difficult to find in the documentation but its this: 


```

python3 -m pip install --index-url https://registry.intersystems.com/pypi/simple --no-cache-dir --target /usr/irissys/mgr/python intersystems-iris-automl

```

That way you no longer need a specific ML docker image to use AutoML.

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