#Artificial Intelligence (AI)

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Artificial Intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions) and self-correction.

Learn more.

Contestant

#InterSystems Demo Games entry

⏯️ Healthcare AI Agent Platform

An AI Agent Platform specifically built for the healthcare industry that requires no technical background to utilize. By simply defining a goal or initiative, a swarm of AI agents will conduct operations to achieve the stated end goal and measure their own efficacy along the way to continuously improve. Healthcare organizations today are facing a myriad of challenges that impact financial and clinical performance. These problems are well known, and there is a general consensus on how many of them can be alleviated with AI. However, healthcare organizations face unique challenges in implementing AI:

  • HIPAA/Regulatory compliance - Data quality & accessibility - Embedding AI into current clinical workflows, i.e. integrating AI in such a way that it does not require clinicians to re-orient their processes. It should complement existing workflows, not disrupt them.
  • Implementation cost/high technical barrier of entry – staff needed to build and maintain AI processes can become expensive
  • Ambiguous ROI calculation – careful considerations must be made to properly measure and understand the efficacy of AI integrations. InterSystems is uniquely positioned to address these challenges, enabling healthcare organizations to implement AI with minimal burden.

Presenters:
🗣 @Daniel Cole, Sales Engineer, InterSystems
🗣 @Jeff Morgan, Sales Engineer, InterSystems
🗣 @Raef Youssef, Sales Engineer, InterSystems
🗣 @Jose Ruperez, Sales Engineer, InterSystems
🗣 @Harry Tong, Solutions Architect, InterSystems
🗣 @Nicholai Mitchko, Sales Engineering Manager, InterSystems

https://www.youtube.com/embed/VC3DmmCK6Pw
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Contestant

#InterSystems Demo Games entry

⏯️ Closing the Scientific Knowledge Gap with AI

For venture capitalists (VCs), evaluating research can be challenging. While researchers typically possess years of training and deep expertise in their field, the VCs tasked with assessing their work often lack domain-specific knowledge. This can lead to incomplete understanding of scientific data and an inability to direct organizational initiatives. To solve this problem, we have designed a solution that empowers VCs with AI-driven due diligence: ResearchExplorer. ResearchExplorer is powered by InterSystems IRIS and GPT-4o to help analyze private biomedical research alongside public sources like PubMed using Retrieval-Augmented Generation (RAG). Users submit natural language queries, and the system returns structured insights, head-to-head research comparisons, and AI-generated summaries. This allows users to bridge expertise gaps while securely protecting proprietary data.

Presenters:
🗣 @Jesse Reffsin, Senior Sales Engineer, InterSystems
🗣 @Lynn Wu, Sales Engineer, InterSystems

https://www.youtube.com/embed/zsV3LhGDP1Q
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Hey Community,

Watch this video to learn about AI Co-Pilot, which simplifies DTL coding and offers personalized assistance which makes it accessible to users with varying levels of technical expertise:

⏯ Accelerate DTL Coding with AI Cloud Service @ Global Summit 2024

https://www.youtube.com/embed/C0YfTYiRqzI
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Contestant

#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.

Presenters:
🗣 @Brad Nissenbaum, Sales Engineer, InterSystems
🗣 @Andrew Wardly, Sales Engineer, InterSystems
🗣 @Fan Ji, Solution Developer, InterSystems
🗣 @Lynn Wu, Sales Engineer, InterSystems

https://www.youtube.com/embed/oJ4wfEOAz50
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☤ 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.

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Contestant

#InterSystems Demo Games entry

⏯️ FHIR-Powered AI Healthcare Assistant

Leverage InterSystems's FHIR SQL Builder to project FHIR data to a dataset for vector embedding, and feed the vector store to a RAG chain with LLM and Chatbot.

🗣 Presenter: @Simon Sha, Sales Architect, InterSystems

https://www.youtube.com/embed/P5JcdjLNvbc
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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.

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Hey Community!

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

⏯ Chaining LLMs for Better Results using Agentic AI

https://www.youtube.com/embed/hAtuAIihBVA
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Hey Community!

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

⏯ Role of Data and Interoperability in Effective AI in Healthcare

https://www.youtube.com/embed/JDdMaI2fnWg
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Hi Community!

We’re excited to announce that several winners of the InterSystems AI Programming Contest have been invited to showcase their projects at the Tech Exchange during InterSystems Ready 2025!

Join us on Wednesday, June 25, to explore innovative, real-world solutions built with InterSystems IRIS, AI, LLMs, and intelligent agent technologies — directly from the developers who created them:

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Introducing Smart Clinical Sidechick — the intelligent, no-drama partner your EHR wishes it could be. She reads FHIR data in real time, interprets lab results without ghosting, and explains clinical alerts like she actually cares. Built with GPT-4 brains and YAML sass, she’s not here to replace your main EHR—just to make it look bad. Tired of irrelevant alerts and cryptic warnings? Sidechick serves up real, explainable insights, not vague “elevated risk” vibes. And when your backend crashes, she doesn’t panic—she self-heals.

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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?

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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!

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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

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Hi Community,

Traditional keyword-based search struggles with nuanced, domain-specific queries. Vector search, however, leverages semantic understanding, enabling AI agents to retrieve and generate responses based on context—not just keywords.

This article provides a step-by-step guide to creating an Agentic AI RAG (Retrieval-Augmented Generation) application.

Implementation Steps:

  1. Create Agent Tools
    • Add Ingest functionality: Automatically ingests and index documents (e.g., InterSystems IRIS 2025.1 Release Notes).
    • Implement Vector Search Functionality
  2. Create Vector Search Agent
  3. Handoff to Triage (Main Agent)
  4. Run The Agent
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Article
· Apr 1 1m read
IRIS-Intelligent Butler

# IRIS-Intelligent Butler
IRIS Intelligent Butler is an AI intelligent butler system built on the InterSystems IRIS data platform, aimed at providing users with comprehensive intelligent life and work assistance through data intelligence, automated decision-making, and natural interaction.
## Application scenarios
adding services, initializing configurations, etc. are currently being enriched
## Intelligent Butler

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I just realized I never finished this serie of articles!

GIF de Shame On You Meme | Tenor

In today's article, we'll take a look at the production process that extracts the ICD-10 diagnoses most similar to our text, so we can select the most appropriate option from our frontend.

Looking for diagnostic similarities:

From the screen that shows the diagnostic requests received in HL7 in our application, we can search for the ICD-10 diagnoses closest to the text entered by the professional.

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Hey Community,

It's time for the first programming contest of the year, and there's a surprise so read on! Please welcome:

🏆 InterSystems AI Programming Contest: Vector Search, GenAI, and AI Agents 🏆

Duration: March 17 - April 6, 2025

Prize pool: $12,000 + a chance to be invited to the Global Summit 2025!

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With the introduction of vector data types and the Vector Search functionality in IRIS, a whole world of possibilities opens up for the development of applications and an example of these applications is the one that I recently saw published in a public contest by the Ministry of Health from Valencia in which they requested a tool to assist in ICD-10 coding using AI models.

How could we implement an application similar to the one requested? Let's see what we would need:

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