#SQL

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SQL is a standard language for storing, manipulating and retrieving data in relational databases.

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Article David Hockenbroch · Feb 25 2m read

Simplified JSON SQL Queries

Inspired by @Ashok Kumar T's post on the ideas portal here as well as my own wishes for a solution to this problem, I have come up with a simple way to allow more complete and consistent JSON queries without having to specify every desired field. I have created a class that extends the built-in %JSON.Adaptor class and makes its %JSONExportToString and %JSONExportToStream methods accessible through SQL with just a couple of simple SqlProc Methods.

Class DH.JSONAdaptor Extends %JSON.Adaptor [ Abstract ]
{
ClassMethod jsonstring(id, map = "") [ SqlProc ]
{
	try{
		set myobj = .
#InterSystems IRIS #InterSystems Package Manager (IPM) #JSON #SQL
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Article Pierre-Yves Duquesnoy · Feb 23 1m read

Your fast path to an InterSystems Certification

The InterSystems Ready 2026 Conference  is approaching fast — it's a great time to prepare and check your knowledge before attempting one of the Certification exams onsite .

InterSystems certifications aren't easy: you need to practice with questions aligned to the real exam objectives.

exam-prep.es is a free platform built for exactly that: practice, identify weak spots, and show up better prepared.

#Documentation #Certification #HL7 #READY 2026 #SQL #System Administration
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Article Alberto Fuentes · Feb 13 10m read

From FHIR Events to Explainable Agentic AI: Building a Clinical Follow‑Up Demo with InterSystems IRIS for Health

10:47 AM — Jose Garcia's creatinine test results arrive at the hospital FHIR server. 2.1 mg/dL — a 35% increase from last month.

What happens next?

  • Most systems: ❌ The result sits in a queue until a clinician reviews it manually — hours or days later.
  • This system: 👍 An AI agent evaluates the trend, consults clinical guidelines, and generates evidence-based recommendations — in seconds, automatically.

No chatbot. No manual prompts. No black-box reasoning.

This is event-driven clinical decision support with full explainability:

image

✅ Triggered automatically by FHIR events ✅ Multi-agent reasoning (context, guidelines, recommendations) ✅ Complete audit trail in SQL (every decision, every evidence source) ✅ FHIR-native outputs (DiagnosticReport published to server)

Built with:

  • InterSystems IRIS for Health — Orchestration, FHIR, persistence, vector search
  • CrewAI — Multi-agent framework for structured reasoning

You'll learn: 🖋️ How to orchestrate agentic AI workflows within production-grade interoperability systems — and why explainability matters more than accuracy alone.

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#InterSystems IRIS for Health #Artificial Intelligence (AI) #FHIR #Generative AI (GenAI) #Interoperability #SQL #Vector Search
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Article Evgeny Shvarov · Feb 16 5m read

Vibecoding Full Stack Applications With IRIS Backend in January 2026

How I Vibecoded a Backend (and Frontend) on InterSystems IRIS

I wanted to try vibecoding a real backend + frontend setup on InterSystems IRIS, ideally using something realistic rather than a toy example. The goal was simple: take an existing, well-known persistent package in IRIS and quickly build a usable UI and API around it — letting AI handle as much of the boilerplate as possible. Here is the result of the experiments.

#InterSystems IRIS #Generative AI (GenAI) #ObjectScript #REST API #SQL #VSCode
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