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#InterSystems IRIS for Health

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InterSystems IRIS for Health™ is the world’s first and only data platform engineered specifically for the rapid development of healthcare applications to manage the world’s most critical data. It includes powerful out-of-the-box features: transaction processing and analytics, an extensible healthcare data model, FHIR-based solution development, support for healthcare interoperability standards, and more. All enabling developers to realize value and build breakthrough applications, fast. Learn more.

Article
· Jul 24, 2023 20m read
Local K8s Deployment of a FHIR server

k8s

This is a sample to deploy iris-oauth-fhir on k3d with IKO.
* iris-oauth-fhir is a sample to deploy a FHIR server with OAuth2 authentication with InterSystems IRIS for Health as a resource server and Google OpenId as an authorization server.
* k3d is a lightweight wrapper to run k3s (Rancher Lab's minimal Kubernetes distribution) in docker.
* IKO is a tool to deploy InterSystems IRIS for Health on Kubernetes.

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Hi Community,

We're pleased to invite you to the upcoming webinar in Hebrew:

👉 Hebrew Webinar: GenAI + RAG - Leveraging Intersystems IRIS as your Vector DB👈

📅 Date & time: February 26th, 3:00 PM IDT

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Hello developers!

We are holding the first technical article contest on Japan's InterSystems Developer Community!

The first contest is a technical document writing contest, and you can submit any content related to the InterSystems IRIS/InterSystems IRIS for Health. (The article must be in Japanese.)

✍ InterSystems Japan Technical Document Writing Contest: Articles related to IRIS ✍

🎁 Participation prize: There will be a participation prize for everyone who submits an article for the contest.

🏆 Special prize: Authors of three selected works will receive special prizes.

Entering the contest is easy! Please post an article related to IRIS on the developer community during the period from Wednesday, September 6, 2023 to Monday, November 6, 2023.

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Hey Community,

Please join the next InterSystems online programming competition:

🏆 InterSystems FHIR Accelerator Programming Contest 🏆

Submit an application that uses InterSystems FHIR-as-a-service on AWS or helps to develop solutions using InterSystems IRIS FHIR Accelerator.

    Duration: May 10 - June 06, 2021

    Total prize: $8,750

    👉 Landing page 👈

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    InterSystems is very pleased to announce the 2021.1 release of InterSystems IRIS Data Platform, InterSystems IRIS for Health and HealthShare Health Connect, which are now Generally Available to our customers and partners.

    The enhancements in this release offer developers more freedom to build fast and robust applications in their language of choice, both server-side and client-side. This release also enables users to consume large amounts of information more effectively through new and faster analytics capabilities.

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    InterSystems is announcing an end of maintenance event for Zen Reports beginning in Intersystems IRIS and IRIS for Health 2025.1. This follows the deprecation notice made when InterSystems IRIS was introduced in 2018 and subsequent inclusion of InterSystems Reports in 2020 to provide replacement reporting functionality. An overview of the timeline is:

    March 2018. InterSystems IRIS 2018.1: Announcement of Zen Reports deprecation, continued shipment to provide continuity for existing applications

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    InterSystems Official
    · Jan 30, 2023
    Updated Vulnerability Handling Policy

    At InterSystems, we believe in the responsible disclosure of recently discovered security vulnerabilities. We provide timely information to our customers, while keeping it out of the hands of people that may misuse it. We also understand each customer has different requirements related to the resolution of security issues.

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    Article
    · Jan 29, 2024 12m read
    Creating custom login pages with %CSP.Login

    The %CSP.Login class is the utility class provided by InterSystems IRIS to do custom login pages. If you want to control your IRIS application authentication UI, you must extend %CSP.Login and override some methods according to your needs. This article is going to detail those methods and what you can do with them. In addition to that, you will get an explanation of the delegated authentication mechanism provided by ZAUTHENTICATE.mac routine.

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    An extension “extends” or enhances a FHIR resource or a data element in a custom way. The extension can be added to the root of a resource, such as “Patient.ethnicity” in US Core profile, and they can be added to individual elements such as HumanName, Address or Identifier.

    Did you know that you can also add an extension to a primitive data type?

    Primitives usually store a single item and are the most basic element in FHIR. For example: "Keren", false, 1234, 12/08/2024 etc.

    For example, the patient resources might look like this:

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    I am demonstrating a use case of how we can create an IRIS Interoperability Production for special use in an external language. InterSystems IRIS, within Interoperability has a framework called Production Extension (PEX), using which we can create productions and program them as per their purpose using external languages like Java, Python etc, and also develop custom inbound and outbound adapters to communicate with other applications.

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    ​Keywords: ChatGPT, COS, Lookup Table, IRIS, AI

    Purpose


    Here is another quick note before we move on to GPT-4 assisted automation journey. Below are some "little" helps ChatGPT had already been offering, here and there, during daily works.

    And what could be the perceived gaps, risks and traps to LLMs assisted automation, if you happen to explore this path too. I'd also love to hear anyone's use cases and experiences on this front too.

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    The rise of Big Data projects, real-time self-service analytics, online query services, and social networks, among others, have enabled scenarios for massive and high-performance data queries. In response to this challenge, MPP (massively parallel processing database) technology was created, and it quickly established itself. Among the open-source MPP options, Presto (https://prestodb.io/) is the best-known option. It originated in Facebook and was utilized for data analytics, but later became open-sourced.

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    Article
    · Mar 3, 2021 4m read
    Access to IRIS from Rust

    What do you think If I will say you, that very soon you will be able to connect to IRIS from the application written in Rust.

    What is Rust

    Rust is a multi-paradigm programming language designed for performance and safety, especially safe concurrency. Rust is syntactically similar to C++, but can guarantee memory safety by using a borrow checker to validate references. Rust achieves memory safety without garbage collection, and reference counting is optional. (c) Wikipedia

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    Hello everybody! We’re happy to announce a new way to download Community Edition kits of InterSystems IRIS and IRIS for Health. The Community Edition is a no-cost developer edition that makes it easy to start developing solutions with IRIS. You can now download these kits through the Evaluation service: evaluation.intersystems.com.

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    image

    Hi Community,
    In this article, I will demonstrate below steps to create your own chatbot by using spaCy (spaCy is an open-source software library for advanced natural language processing, written in the programming languages Python and Cython):

    • Step1: Install required libraries

    • Step2: Create patterns and responses file

    • Step3: Train the Model

    • Step4: Create ChatBot Application based on the trained model

    So Let us start.

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    In the previous article we presented the d[IA]gnosis application developed to support the coding of diagnoses in ICD-10. In this article we will see how InterSystems IRIS for Health provides us with the necessary tools for the generation of vectors from the ICD-10 code list using a pre-trained language model, its storage and the subsequent search for similarities on all these generated vectors.

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    Introduction

    InterSystems has recently completed a performance and scalability benchmark of IRIS for Health 2020.1, focusing on HL7 version 2 interoperability. This article describes the observed throughput for various workloads, and also provides general configuration and sizing guidelines for systems where IRIS for Health is used as an interoperability engine for HL7v2 messaging.

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    Introduction

    We are in the age of the multiplatform economy and APIs are the "glue" in this digital scenario. Since they are so important, they are seen by developers as a service or product to be consumed. Therefore, usage experience is a crucial factor for its success.

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