Hey Community!

We're happy to share the next video in the "Code to Care" series on our InterSystems Developers YouTube:

⏯  From Words to Molecules: How AI Is Transforming Medicine and Beyond

Hi, 

We very much appreciate the interest in the Developer Community for IRIS Vector Search and hope our technology has helped many of you build innovative applications or advanced your R&D efforts. With a dedicated index, integrated embeddings generation, and deep integration with our SQL engine now available in InterSystems IRIS, we're looking at the next frontier, and would love to hear your feedback on the technology to prioritize our investments.

Introduction

This anthropic article made me think of several InterSystems presentations and articles on the topic of data quality for AI applications. InterSystems is right that data quality is crucial for AI, but I imagined there would be room for small errors, but this study suggests otherwise. That small errors can lead to big hallucinations. What do you think of this? And how can InterSystems technology help?

https://www.anthropic.com/research/small-samples-poison

Hey Community!

We're happy to share the next video in the "Code to Care" series on our InterSystems Developers YouTube:

⏯  Before the Lightbulb: Understanding the First Phase of the AI Revolution in Medicine

Hi Community,

We’re excited to share a brand-new Instruqt tutorial: 

🧑‍🏫 RAG using InterSystems IRIS Vector Search

This hands-on lab walks you through building a Retrieval Augmented Generation (RAG) AI chatbot powered by InterSystems IRIS Vector Search. You’ll see how vector search can be leveraged to deliver up-to-date and accurate responses, combining the strengths of IRIS with generative AI.

✨ Why try it?

Vanna.AI - Personalized AI InterSystems OMOP Agent

In the previous article, we saw how to build a customer service AI agent with smolagents and InterSystems IRIS, combining SQL, RAG with vector search, and interoperability.

In that case, we used cloud models (OpenAI) for the LLM and embeddings.

This time, we’ll take it one step further: running the same agent, but with local models thanks to Ollama.

Plug-N-Play on Pattern Match WorkBench

Article to announce pre-built pattern expressions are available from demo application.

AI deducing patterns require ten and more sample values to get warmed up.

The entry of a single value for a pattern has therefore been repurposed for retrieving pre-built patterns.

Example: Email address

Paste an sample value for example an email address in description and press "Pattern from Description".

The sample is tested against available built-in patterns and any matching patterns and descriptions are displayed.

#InterSystems Demo Games entry

⏯️ Autonomous Business Intelligent Clerk (ABiC) - Combining InterSystems BI and Generative AI

Hey Community!

We're happy to share the next video in the "Code to Care" series on our InterSystems Developers YouTube:

⏯  Can AI Fix Bugs? Evaluating Progress and Challenges

Hey Community!

We're happy to share the next video in the "Code to Care" series on our InterSystems Developers YouTube:

⏯  Can AI Fix Bugs? Inside the Benchmarking Effort

If you’ve ever watched a true artisan—whether a potter turning mud into a masterpiece or a luthier bringing raw wood to life as a marvelous guitar—you know that magic isn’t in the materials, but in care, craft, and process. I know this firsthand: my handmade electric guitar is a daily inspiration, but I’ll admit—creating something like that is a talent I don’t have.

I am brand new to using AI. I downloaded some medical visit progress notes from my Patient Portal. I extracted text from PDF files. I found a YouTube video that showed how to extract metadata using an OpenAI query / prompt such as this one:

ollama-ai-iris/data/prompts/medical_progress_notes_prompt.txt at main · oliverwilms/ollama-ai-iris
 

I combined @Rodolfo Pscheidt Jr https://github.com/RodolfoPscheidtJr/ollama-ai-iris with some files from @Guillaume Rongier https://openexchange.intersystems.com/package/iris-rag-demo.

I attempted to run

Thirteen years ago, I attained dual undergraduate degrees in electrical engineering and math, then promptly started full-time at InterSystems using neither. One of my most memorable and stomach-churning academic experiences was in Stats II. On an exam, I was solving a moderately difficult confidence interval problem. I was running out of time, so (being an engineer) I wrote out the definite integral on the exam paper, punched it into my graphing calculator, wrote an arrow with “calculator” over it, then wrote the result. My professor, affectionately known as “Dean, Dean, the Failing Machine,”

Hey Community!

We're happy to share the next video in the "Code to Care" series on our InterSystems Developers YouTube:

⏯  Can AI fix bugs? The setup

Audience

Those curious in exploring new GenerativeAI usecases.

Shares thoughts and rationale when training generative AI for pattern matching.

Challenge 1 - Simple but no simpler

A developer aspires to conceive an elegant solution to requirements.
Pattern matches ( like regular expressions ) can be solved for in many ways. Which one is the better code solution?
Can an AI postulate an elegant pattern match solution for a range of simple-to-complex data samples?

Consider the three string values:

• "AA"
• "BB"
• "CC"

Hey Community!

We're happy to share the next video in the "Code to Care" series on our InterSystems Developers YouTube:

⏯  Agentic AI in Action: Building a Decision-Making Loop with LLMs

#InterSystems Demo Games entry

⏯️ Care Compass – InterSystems IRIS powered RAG AI assistant for Care Managers

Care Compass is a prototype AI assistant that helps caseworkers prioritize clients by analyzing clinical and social data. Using Retrieval Augmented Generation (RAG) and large language models, it generates narrative risk summaries, calculates dynamic risk scores, and recommends next steps. The goal is to reduce preventable ER visits and support early, informed interventions.

☤ Care 🩺 Compass 🧭 - Proof-of-Concept - Demo Games Contest Entry

Introducing Care Compass: AI-Powered Case Prioritization for Human Services

In today’s healthcare and social services landscape, caseworkers face overwhelming challenges. High caseloads, fragmented systems, and disconnected data often lead to missed opportunities to intervene early and effectively. This results in worker burnout and preventable emergency room visits, which are both costly and avoidable.

Care Compass was created to change that.

Thank you community for translating an earlier article into Portuguese.
Am returning the favor with a new release of Pattern Match Workbench demo app.

Added support for Portuguese.

The labels, buttons, feedback messages and help-text for user interface are updated.

Pattern Descriptions can be requested for the new language.

The single AI Model for transforming user prompt into Pattern match code was fully retrained.

Values to Pattern Code Model also retrained

INTRO

My use case is I want AI to extract six pieces of key information from medical visit notes.

It works okay with notes from Epic patient portals. I am struggling with one of my own visit Summaries. So far I have not been able to instruct ollama to give me a JSON response where it gave me what I am asking for.

My original medical_progress_notes_prompt was:

Medical progress note:
---
(document)
---

You are an expert in analyzing medical progress notes. Please carefully read the provided progress note above and extract the following key information:

Audience

Those curious in exploring new GenerativeAI usecases.

Developers and analysts looking for a quick way to tame the Pattern Match operator.

In both ObjectScript and SQL this has a quite visually dense format.

if booking?2A1"-"1(1"CARD",1"RAD")1.5N

SELECTDISTINCT PatientRef
FROM APPOINTMENT.BOOKING
WHERE Active='Y'AND
LocationCode %PATTERN '2A1"-"1(1"CARD",1"RAD")1.5N'

Challenge

Use generative AI to assist create and modify pattern match code from different natural language input.

Artificial Intelligence (AI) is getting a lot of attention lately because it can change many areas of our lives. Better computer power and more data have helped AI do amazing things, like improving medical tests and making self-driving cars. AI can also help businesses make better decisions and work more efficiently, which is why it's becoming more popular and widely used. How can one integrate the OpenAI API calls into an existing IRIS Interoperability application?

Hi developers!

This will be a very short article as in April 2025 with Lovable and other Prompt-to-UI tools it becomes possible to build the frontend with prompting. Even to the folks like me who is not familiar with modern UI techics at all.

Well, I know at least the words javascript, typescript and ReactJS, so in this very short article we will be building the ReactJS UI to InterSystems FHIR server with Lovable.ai.

Let's go!

I combined @Rodolfo Pscheidt https://github.com/RodolfoPscheidtJr/ollama-ai-iris with some files from @Guillaume Rongier https://openexchange.intersystems.com/package/iris-rag-demo.

My own project is https://github.com/oliverwilms/ollama-ai-iris

I can run load_data.py and it connects to IRIS (same container).

When I try to run query_data.py https://github.com/oliverwilms/ollama-ai-iris/blob/main/query_data.py , it cannot connect to ollama:

ConnectionError: Failed to connect to Ollama. Please check that Ollama is downloaded, running and accessible.

Hi, colleagues!

As you can see the new topic of the programming contest - AI Agents. 

The topic was over-hyped recently on the Internet and has different meanings. You might get curious about what we mean by AI agents in regard to the InterSystems programming contest.

Hi Developers!

We are happy to present the bonuses page for the applications submitted to the InterSystems AI Programming Contest!

See the results below.

See the Langchain IRIS Tool in action on YouTube. You can see IRIS metrics, discover classes, generate fake data, and so on. Project using Ollama, IRIS VectorDB, Streamlit and Langchain.