#Contest

Hi Community!

We're pleased to invite you to the Online meetup with the winners of the InterSystems Full Stack contest!

Date & Time: Friday, October 16, 2020 – 11:00 EDT

What awaits you at this virtual Meetup?

• Our winners' bios.
• Short demos on their applications.
• An open discussion about technologies being used, bonuses, questions. Plans for the next contests.

Hey Developers!

This week is a voting week for the InterSystems Full Stack Contest!

So, it's time to give your vote to the best solutions built with InterSystems IRIS.

🔥 You decide: VOTING IS HERE 🔥

How to vote? This is easy: you will have one vote, and your vote goes either in Experts Nomination or in Community Nomination.

Hey Developers!

We're pleased to announce the next competition of creating open-source solutions using InterSystems IRIS! Please welcome:

⚡️ InterSystems Full Stack Contest ⚡️

Duration: September 21 - October 11, 2020

Hi Developers!

Here're the technology bonuses for the Full Stack Contest that will give you extra points in the voting:

• InterSystems IRIS REST API Usage
• InterSystems Native API Usage
• InterSystems JDBC Usage
• Unit Testing
• ZPM Package deployment
• Docker container usage

See the details below.

Hi Developers!

The InterSystems IRIS for Health FHIR Contest is over. Thank you all for participating in our FHIR Competition!

And now it's time to announce the winners!

A storm of applause goes to these developers and their applications:

The fhir-react project defines a unique component which renders the interface based on FHIR resource type. There's no need for any configuration because the library uses the standard of defined by the resource type.

So, I decided to apply the same idea, but for charts. The basic idea is depicted below:

Hi Developers!

Here're the technology bonuses for the FHIR programming contest that will give you extra points in the voting:

• FHIR Server REST API usage
• The usage of SQL Schema of FHIR Resources
• Healthcare standards data transformation
• Docker container usage

See the details below.

Hey Developers!

Want to participate again in the competition of creating open-source solutions using InterSystems IRIS Data Platform? Please welcome:

➡️ InterSystems IRIS for Health FHIR Contest ⬅️

Duration: August 10-30, 2020

Hi Community!

We are pleased to invite all the developers to the upcoming InterSystems IRIS for Health FHIR Contest Kick-Off Webinar! The topic of this webinar is dedicated to the FHIR Programming Contest.

On this webinar, we will talk and demo how to use the IRIS-FHIR-Template to build FHIR solutions using InterSystems IRIS for Health.

Date & Time: Tuesday, August 11 — 11:00 AM EDT

Speakers:
🗣 @Evgeny Shvarov, InterSystems Developer Ecosystem Manager
🗣 @Guillaume Rongier, InterSystems Sales Engineer
🗣 @Patrick Jamieson, InterSystems Product Manager - Health Informatics Platform

What awaits you at this webinar?

In the past, reading information from a bar code was limited to a simple alphanumeric code. The creation of a bar code with more than one dimension (2D), especially the QR Code, allowed to increase the amount and variety of data stored in a bar code. While conventional bar codes are capable of storing a maximum of approximately 20 digits, the QR Code is capable of handling several tens to hundreds of times more information. This revolutionized the markets. Now QR codes are everywhere and can be very useful for storing textual, numeric, alphanumeric and even binary data.

Hi Developers!

The InterSystems IRIS AI Contest is over. Thank you all for participating in our IRIS AI Competition!

And now it's time to announce the winners!

A storm of applause goes to these developers and their applications:

Currently, the process of using machine learning is difficult and requires excessive consumption of data scientist services. AutoML technology was created to assist organizations in reducing this complexity and the dependence on specialized ML personnel.

AutoML allows the user to point to a data set, select the subject of interest (feature) and set the variables that affect the subject (labels). From there, the user informs the model name and then creates his predictive or data classification model based on machine learning.

Hi Community,

Please welcome the new video, specially recorded by @Renato Banzai for the InterSystems IRIS AI Programming Contest:

⏯ IRIS ML Suite Demo

https://www.youtube.com/embed/3-YSnFQnMLU
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A few months ago, I read this interesting article from MIT Technology Review, explaing how COVID-19 pandemic are issuing challenges to IT teams worldwide regarding their machine learning (ML) systems.

Such article inspire me to think about how to deal with performance issues after a ML model was deployed.