#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.

☤ 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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#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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#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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#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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#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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#InterSystems Demo Games entry

⏯️ Text-to-SQL and MQTT Monitoring

A text-to-sql demo on mqtt data analytics with RAG.

🗣 Presenter: @jieliang liu, Sales Engineer, InterSystems

https://www.youtube.com/embed/QqTGk6eiPXA
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