Article Jorge Jaramillo Herrera · May 5 19m read

Explainability in ML Models

This article introduces SHAP explainability methods as an approach to understand the reasons behind predictions in machine learning black-box models. It also includes a simple Jupyter notebook that you can use and modify to gain hands-on experience with these concepts:

https://www.kaggle.com/code/jorgeivnjh/explainability-in-ml-models

https://github.com/JorgeIvanJH/Explainability-in-ML-models

We will leverage these concepts for a future implementation in our Continuous Training Pipeline: https://community.intersystems.com/post/complementing-iris-mlflow-continuous-training-ct-pipeline

#Other #Artificial Intelligence (AI) #Machine Learning (ML) #Python
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Article Jonathan Card · May 28 5m read

ClassMethods Are Not Your Friends

There seems to be a generous use of ClassMethods in ObjectScript code generally. I hope my own experiences aren't representative, but I bet they are. Forgive me for giving away the ending of this article, but in short: don't use them. Unless you can make a pretty convincing case that you have to, just never use them.1

What is a ClassMethod? In an ObjectScript class, you can define methods in two different ways: in a Method, you must instantiate an instance of the class to call the method, and in a ClassMethod, you can call the method without instantiating the class. Of course, in a ClassMethod, you don't have access to any properties of the object (because there's no object), but you can access globals (they are global, after all) and Parameters (which are class constants).

#InterSystems IRIS #Globals #ObjectScript #Testing
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Article Sean Connelly · 2 hr ago 1m read

FHIR Agent Studio Demo

 

I’m pleased to share a demo of FHIR Agent Studio, now available on YouTube.

FHIR Agent Studio Demo

https://www.youtube.com/watch?v=vktfq_kvNnk

FHIR Agent Studio brings AI agents together with FHIR, InterSystems IRIS, Vector Search, and large language models to demonstrate how developers can explore, build, and test agent-driven healthcare workflows.

You can also find more information here:

Introduction article: https://community.intersystems.com/post/introducing-fhir-agent-studio-ai-agents-fhir-intersystems-iris

GitHub repository: https://github.com/SeanConnelly/ai-studio-for-fhir

#Health Connect #Artificial Intelligence (AI) #FHIR #Large Language Model (LLM) #Vector Search
Open Exchange
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Announcement Admin GlobalMasters · 5 hr ago

June Article Bounty Topics


Hey! June Article Bounty is live on Global Masters! ☀️🚀

Submit a brand-new article on one of the announced topics and earn a bounty of 🏆 5,000 Global Masters points once it’s approved! 🎉

Here’s the list of June topics:

#Global Masters
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Article José Pereira · 5 hr ago 20m read

Using InterSystems IRIS FHIR Server, MCP, and Generative AI to Assist Pre-Consultation Care

An AI agent reads the FHIR patient record before the consultation, asks the right questions based on what it already knows, detects critical red flags, and writes its findings back — so the physician arrives prepared.

Healthcare Pain Points Addressed

Before a patient walks into a consultation room, a critical failure has already occurred: nobody read their medical history. The physician has 15 minutes. The patient repeats their conditions, medications, and allergies for the third time that year.

#InterSystems IRIS #InterSystems IRIS for Health #Open Exchange #Artificial Intelligence (AI) #Docker #FHIR #Generative AI (GenAI) #Python
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Article Alfaxad Eyembe · 9 hr ago 6m read

Introducing Sara: A Clinical Workflow Agent

Sara is my entry for the InterSystems AI Agents for FHIR contest. Feel free to try out Sara and vote for Sara on the contest page.

https://youtu.be/UAjI9O848wU?si=BWTVk9gsV4xTOlUj

Physicians spend only 47% of their work time on direct patient care [1]. The rest goes to EHR administrative tasks: order entry, documentation, prior authorizations, with 43% of their time spent on a clinical computer [2]

#InterSystems IRIS for Health #Artificial Intelligence (AI) #Generative AI (GenAI)
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Question Anderson Negreli · Mar 25, 2021

How to get the row number in an SQL query?

Hi,

I'm doing a query in SQL and I need to sort my data by some non-repeated field.

Unfortunately, my data is grouped in a way that I cannot guarantee that any column will not have repeated data, so one solution would be to take the row number.

Also, the Cache is not accepting Row_Number () in my querry and I would like to know if there is another solution to return line numbers or some way to add this function to the Cache.

Best regards.

#Caché #SQL
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Article Sean Connelly · Jun 7 7m read

Introducing FHIR Agent Studio: AI agents for FHIR on InterSystems IRIS

AI is going to change healthcare, but only if clinicians can trust it and developers can build it without reinventing the plumbing every time. FHIR Agent Studio is my attempt at both: a place to build AI agents for FHIR workflows from reusable building blocks, run them on a real InterSystems IRIS for Health backend, and inspect exactly what each one did at every step.

It is my entry in the InterSystems AI Agents for FHIR contest, and it ships with twelve working agents over a synthetic FHIR repository of around 1,000 patients and 20,000 resources.

#Health Connect #Artificial Intelligence (AI) #FHIR
Open Exchange
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Article Pietro Di Leo · Oct 9, 2025 6m read

Enhancing FHIR Data Exploration with Local LLMs: Integrating IRIS and Ollama

Introduction

In my previous article, I introduced the FHIR Data Explorer, a proof-of-concept application that connects InterSystems IRIS, Python, and Ollama to enable semantic search and visualization over healthcare data in FHIR format, a project currently participating in the InterSystems External Language Contest.

In this follow-up, we’ll see how I integrated Ollama for generating patient history summaries directly from structured FHIR data stored in IRIS, using lightweight local language models (LLMs) such as Llama 3.2:1B or Gemma 2:2B.

The goal was to build a completely local AI pipeline that can extract, format, and narrate patient histories while keeping data private and under full control.

All patient data used in this demo comes from FHIR bundles, which were parsed and loaded into IRIS via the IRIStool module. This approach makes it straightforward to query, transform, and vectorize healthcare data using familiar pandas operations in Python. If you’re curious about how I built this integration, check out my previous article Building a FHIR Vector Repository with InterSystems IRIS and Python through the IRIStool module.

Both IRIStool and FHIR Data Explorer are available on the InterSystems Open Exchange — and part of my contest submissions. If you find them useful, please consider voting for them!

#InterSystems IRIS #Artificial Intelligence (AI) #FHIR #Large Language Model (LLM) #Prompt Engineering #Python
Open Exchange
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Article Carlos Eduardo Dias Duarte · Jun 7 5m read

Smart Discharge Navigator: An AI Agent for Hospital Readmission Risk - Built on IRIS for Health - Hospital readmissions cost the US healthcare system $17 billion annually.

Smart Discharge Navigator: An AI Agent for Hospital Readmission Risk — Built on IRIS for Health

Hospital readmissions cost the US healthcare system $17 billion annually. A significant portion of those readmissions are preventable — but only if the right information reaches the right clinician at the right moment: at discharge.

That's the problem I set out to solve with Smart Discharge Navigator, my entry for the InterSystems Programming Contest: AI Agents for FHIR 2026.

#InterSystems IRIS for Health #Open Exchange #Analytics #Artificial Intelligence (AI) #Contest #Docker #FHIR #Interoperability #Python #React
Open Exchange
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Discussion Evgeny Shvarov · Jun 5

Migrations in IRIS. How are you managing it?

Hi folks!

Suppose a new version of your amazing software solution built on IRIS needs some persistence change: some data needs to be converted, some classes get new properties or even renamed, and some data should be prepopulated for newly introduced persistent classes to keep the whole application data consistent.

What are your approaches? 

SQL-based scripts? ObjectScript, or Python? for both directions of migration, up and down? 

Do you autogenerate it with Claude/Codex? What about data-consistency tests?

COuld you please share your thoughts? or libraries?

#InterSystems IRIS #Data Model #Database Transaction Processing
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Article Mainza Kangombe · Jun 6 4m read

The Claims We Don’t Notice (And the Systems That Do)

Healthcare billing isn’t a pipeline. It’s a conversation about trust. 

Every day, millions of clinical transactions flow from doctors’ keyboards to insurance ledgers. Standard health IT systems are built to count these transactions. They store them. They organize them. 

They route them. But standard systems don't notice them. 

We’ve built faster and faster databases to process claims, but we forgot to ask: Does this claim make sense? 

Because we don’t ask in real-time, we’ve accepted a compromise. We pay first, wait six months, and then hire forensic auditors to find the mistakes.

#InterSystems IRIS for Health #Access control #Dashboards #Databases #FHIR #Graph #Mapping #Performance #Security #Video
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Article Robert Cemper · Apr 28, 2023 4m read

45 years with InterSystems 1978 - 2023

I decided to write this down before time wiped out my memory
It's a very personal story as a partner, as a competitor, as an employee,
as a customer and finally as an external observer of InterSystems.

#Other
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Article Robert Cemper · Aug 26, 2017 3m read

From The Roots to InterSystems

This is a  rather personal view of the history before Caché.
It is in no sense meant to compete with the excellent books from Mike Kadow discussed in an earlier article.
We have different histories and so this is meant to create a different perspective of the past.

The whole story started in 1966 at MGH (Mass.General Hospital) on a PDP-7 Ser.#103
with 8K of memory (18-bit words) [today = 18K byte ]  as a spare system.

"Serial Number 103 - was located in the basement of the now demolished Thayer Building,
currently [2014] the site of the Cox Cancer Center at MGH.

#Caché #InterSystems IRIS
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Article Kate Lau · Oct 13, 2025 5m read

REST api example for decode a Base64 data

Hi all,

It's me again 😁. In the pervious article Writing a REST api service for exporting the generated FHIR bundle in JSON, we actually generated a resource DocumentReference, with the content data encoded in Base64

Question!! Is it possible to write a REST service for decoding it? Because I am very curious what is the message data talking about🤔🤔🤔

OK, Let's start!

1. Create a new utility class datagen.utli.decodefhirjson.cls for decoding the data inside the DocumentReference
 

ClassExtends%RegisteredObject

2. Write a Python function decodebase64docref to 
a. loop through the FHIR bundle
b.

#InterSystems IRIS #InterSystems IRIS for Health #Embedded Python #FHIR #JSON #Python #REST API
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