How many times have you had to receive or generate a JSON and wished you could work on it using DTLs without having to deal with DynamicObjects trying to remember the name of each field? Do you want to break down and make your giant JSON file more digestible?

In my case, never, but I thought that someone might find it useful to have a feature that captures your JSON and breaks it down into a series of ObjectScript classes that you can work with more easily and conveniently.

Well then...behold JSON2Class in all its glory!

Yes, yes! Welcome! You haven't made a mistake, you are in your beloved InterSystems Developer Community in Spanish.

You may be wondering what the title of this article is about, well it's very simple, today we are gathered here to honor the Inquisitor and praise the great work he performed. 

So, who or what is the Inquisitor?

Perfect, now that I have your attention, it's time to explain what the Inquisitor is. The Inquisitor is a solution developed with InterSystems technology to subject public contracts published daily on the platform  https://contrataciondelestado.es/ to scrutiny.

Welcome, dear members of the Community!

In this article, we will present an example of a project implementing a FHIR-based solution. This project will be based on the national project (Spanish national project), known as ÚNICAS.

What is ÚNICAS?

In his own words:

A project whose objective is to create an ecosystem of partnerships to improve healthcare for pediatric patients with complex rare diseases (RMDs). This project is being implemented through the network within the National Health System (NHS) to improve the diagnosis and care of patients with rare diseases.

Greetings dear community members!

Many of you will remember the NLP capabilities available in IRIS under the name iKnow, which were deprecated not long ago. But...is everything deprecated? NO! A small village resists deprecation: iFind indexes!

You've probably encountered the terms Data Lake, Data Warehouse, and Data Fabric everywhere over the last 10-15 years. Everything can be solved with one of these three things, or a combination of them ( here and here are a couple of articles from our official website in case you have any doubts about what each of these terms means).

Hello, dear members of our developer community!

In today's article, we're going to take a look at one of the latest remote monitoring features that have been added to the product for our IRIS instances. I'm talking about OpenTelemetry support.

I recently had to refresh my knowledge of the HealthShare EMPI module and since I've been tinkering with IRIS's vector storage and search functionalities for a while I just had to add 1 + 1.

For those of you who are not familiar with EMPI functionality here's a little introduction:

Enterprise Master Patient Index

In general, all EMPIs work in a very similar way, ingesting information, normalizing it and comparing it with the data already present in their system.

It's been a while since the new UI for Productions and DTL was published as a preview and I would like to know your opinions about it.

WARNING: This is a personal opinion, totally personal and not related with InterSystems Corporation.

I'm going to start with the Interoperabilty screen:

Production screen:

The style is sober and without frills, following the line of cloud services design, I like it.

But, always a but...or maybe two:

In my opinion there is too much information, the left menu is superfluous, it's true that you can collapse it, but I don't want to do it each time that I use the

Who hasn't been developing a beautiful example using a Docker IRIS image and had the image generation process fail in the Dockerfile because the license under which the image was created doesn't contain certain privileges?

In my case, what I was deploying in Docker is a small application that uses the Vector data type. With the Community version, this isn't a problem because it already includes Vector Search and vector storage. However, when I changed the IRIS image to a conventional IRIS (the latest-cd), I found that when I built the image, including the classes it had generated, it returned this error:

I just realized I never finished this serie of articles!

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.

To speed up the search process, we stored the vectorized text of the diagnosis received at the time of capturing the HL7 message in our database.

As you may know, the so-called Private Web Server that came with every IRIS installation has been eliminated, making an external web server necessary.

For Docker deployments, it's most common to use the webgateway image (available here) along with the IRIS image to seamlessly access the management portal. This image can be configured to access via HTTPS without any issues by configuring the certificates.

Problem 1: Unable to verify the first certificate

Your SSL connection through the web gateway may have a self-signed certificate configured, and Visual Studio Code is attempting to verify it.

Since the introduction of Embedded Python there has always been doubt about its performance compared to ObjectScript and on more than one occasion I have discussed this with @Guillaume Rongier , well, taking advantage of the fact that I was making a small application to capture data from public competitions in Spain and to be able to perform searches using the capabilities of VectorSearch I saw the opportunity to carry out a small test.

Hi beloved members of the Community!

It is very common in the daily life of IRIS or Health Connect users that it is necessary to install new instances or update the ones they already have and in many cases it is not these same users who carry out the installation, but rather systems personnel who often do not take into account the particularities of the assignment of permissions necessary for the installation.

Greetings dear community members!

I have recently been deploying an IRIS for Health image on a Docker with a preconfigured Webgateway image and I have come across the problem of the SSL configurations that allow us to connect to the IRIS instance using HTTPS and going through our Webgateway.

Until now I had always deployed IRIS for Health with a Community license, which still has the Private Web Server installed, so I only needed to configure the Webgateway connection with the deployed IRIS instance:

Welcome to the third and final publication of our articles dedicated to the development of RAG applications based on LLM models. In this final article, we will see, based on our small example project, how we can find the most appropriate context for the question we want to send to our LLM model and for this we will make use of the vector search functionality included in IRIS.

Vector searches

A key element of any RAG application is the vector search mechanism, which allows you to search within a table with records of this type for those most similar to the reference vector.

We continue with this series of articles on LLM and RAG applications and in this article we will discuss the red boxed part of the following diagram:

In the process of creating a RAG application, choosing an LLM model that is appropriate to your needs (trained in the corresponding subject, costs, speed, etc.) is as important as having a clear understanding of the context you want to provide. Let's start by defining the term to be clear about what we mean by context.

What is context?

You have probably heard a lot about LLMs (Large Language Models) and the associated development of RAG (Retrieval Augmented Generation) applications over the last year. Well, in this series of articles we will explain the fundamentals of each term used and see how to develop a simple RAG application.

What is an LLM?

LLM models are part of what we know as generative AI and their foundation is the vectorization of huge amounts of texts.

Hi community members!

I'm testing some functionalities about Foreign Tables and it works smoothly with PostgreSQL database, but I found out an issue with MySQL database, I followed the documentation:

• Step 1: I've created my SQL Gateway connection to my MySQL database: **WARNING** if the name of the driver file is too long IRIS won't be able to get it.

• Step 2: Create foreign server:
  

  CREATE FOREIGN SERVER Test.MySQLDB FOREIGN DATA WRAPPER JDBC CONNECTION 'MySQL'

• Step 3: Create foreign table:
  

  CREATE FOREIGN TABLE Test.PatientMySQL SERVER Test.MySQLDB TABLE 'patient'

• Step 4: Query Test.

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.

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:

1. List of ICD-10 codes, which we will use as context for our RAG application to search for diagnoses within the plain texts.

Finally and with a little delay, we conclude this series of articles about our Workflow Engine by showing an example of the connection that we could make from a mobile application.

In the previous article we showed the example that we were going to discuss, an application that allows detailed control of a chronic pathology such as hypertension for both the patient and their associated doctor.

Reviewing the different articles that I have published, I realized that I needed to explain a very practical functionality within our EMPI (Enterprise Master Patient Index) and it is none other than the notification of registrations and links to systems external to the EMPI.

This functionality is frankly useful in a tool such as EMPI and especially in environments such as healthcare in which it is very common for the same patient to have their data duplicated in different systems and in the end it is necessary to uniquely identify it.

In our previous article we presented the general concepts as well as the problem that we wanted to solve by using the task engine integrated in InterSystems IRIS, in today's article we will see how we configure an interoperability production to provide a solution.

Workflow Engine Configuration

First we are going to define the roles of the tasks that we are going to manage, in our example we are going to define two types:

• AutomaticBloodPressureRole: to create automatic tasks that will have no intervention from the user.

For some time I have been planning to do some type of proof of concept with the Workflow functionality, which, like so many other functionalities present in IRIS, tends to go quite unnoticed by our clients (and for which I say mea culpa). That's why I decided a few days ago to develop an example of how to configure and exploit this functionality by connecting it with a user interface developed in Angular.

To avoid a very long article and make it more accessible, I am going to divide it into 3.

As you have seen in the latest community publications, InterSystems IRIS has included since version 2024.1 the possibility of including vector data types in its database and based on this type of data vector searches have been implemented. Well, these new features reminded me of the article I published a while ago that was based on facial recognition using Embedded Python.

Introduction

For those of you who don't remember what that article was about, it is linked at the end of this article.

We recently uploaded to OpenExchange a small application that I developed a while ago (and that @Jose-Tomas Salvador improved and refined) that I often use when I need to generate large volumes of HL7 messaging.

The application is developed in NodeJS and works by generating patient and doctor data from seed files that you can modify to your liking to personalize the generated patients. The application will use the generated patients to prepare different types of HL7 messages. At the moment the application can generate the following types of messages.

As most of you probably already know, since approximately the end of 2022 InterSystems IRIS included the columnar storage functionality to its database, well, in today's article we are going to put it to the test in comparison to the usual row storage.

Columnar Storage

What is the main characteristic of this type of storage?

We conclude this series of SMART On FHIR articles with Auth0 and InterSystems IRIS FHIR Repository by reviewing our application developed in Angular 16.

Let's remember what the architecture defined for our solution is like:

Our front-end application corresponds to the second column and as you can see it will be in charge of two things:

1. Redirect the login request to Auth0 and receive the response.
2. Send and receive the response of requests via REST sent to the FHIR server.

In the last article we presented the architecture of our SMART On FHIR project, so it's time to get down to business and start configuring all the elements that we are going to need.

We will first start with Auth0.

AUTH0 configuration

We will start by creating an Auth0 account with a valid email, once registered we will have to create our first application, and we will do it from the menu on the left:

In our example, the application will be of the Single Page Web Application type as it is an application developed in Angular 16. We select this option and click Create.

Introduction

I recently participated in a fantastically organized hands-on by @Patrick Jamieson in which an Angular application was configured together with an IRIS FHIR server following the protocols defined by SMART On FHIR and I found it really interesting, so I decided to develop my own Angular application and thus take advantage of what I learned to publish it in the Community.

SMART On FHIR

Let's see what Google tells us about SMART On FHIR:

SMART on FHIR is a data standard that allows applications to access information in electronic health record (EHR) systems.