What is Distributed Artificial Intelligence (DAI)?

Attempts to find a “bullet-proof” definition have not produced result: it seems like the term is slightly “ahead of time”. Still, we can analyze semantically the term itself – deriving that distributed artificial intelligence is the same AI (see our effort to suggest an “applied” definition) though partitioned across several computers that are not clustered together (neither data-wise, nor via applications, not by providing access to particular computers in principle). I.e., ideally, distributed artificial intelligence should be arranged in such a way that none of the computers participating in that “distribution” have direct access to data nor applications of another computer: the only alternative becomes transmission of data samples and executable scripts via “transparent” messaging. Any deviations from that ideal should lead to an advent of “partially distributed artificial intelligence” – an example being distributed data with a central application server. Or its inverse. One way or the other, we obtain as a result a set of “federated” models (i.e., either models trained each on their own data sources, or each trained by their own algorithms, or “both at once”).

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Hey Community,

We're pleased to invite you to the InterSystems AI+ML Summit 2021, which will be held virtually from January 25 to February 4! Join us for a two-week event that ranges from thought leadership to technical sessions and even 1:1 “Ask the Expert” sessions.

The sessions will be in both German and English. And this summit is free to attend!

See details below:

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Artificial intelligence has solved countless human challenges – and medical coding might be next.
As organizations prepare for ICD-11, medical coding is about to become more complicated. Healthcare organizations in the United States already manage 140,000+ codes in ICD-10. With ICD-11, that number will rise.
Some propose artificial intelligence as a solution. AI could aid computer-based medical coding systems, identifying errors, enhancing patient care, and optimizing revenue cycles, among other benefits.

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Hi Community,

We're pleased to invite you to the online meetup with the winners of the InterSystems Analytics Contest!

Date & Time: Monday, January 4, 2021 – 10:00 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.

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Hey Developers,

This week is a voting week for the InterSystems Analytics 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?

Please meet the new voting engine and algorithm for the Experts and Community nomination:

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Hi Community!

We are pleased to invite all the developers to the upcoming InterSystems Analytics Contest Kick-off Webinar! The topic of this webinar is dedicated to the Analytics contest.

On this webinar, we’ll demo the iris-analytics-template and answer the questions on how to develop, build, and deploy Analytics applications using InterSystems IRIS.

Date & Time: Monday, December 7 — 12:00 PM EDT

Speakers:
🗣 @Carmen Logue, InterSystems Product Manager - Analytics and AI
🗣 @Evgeny Shvarov, InterSystems Developer Ecosystem Manager

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Keywords: IRIS, IntegratedML, Machine Learning, Covid-19, Kaggle

Purpose

Recently I noticed a Kaggle dataset for the prediction of whether a Covid-19 patient will be admitted to ICU. It is a spreadsheet of 1925 encounter records of 231 columns of vital signs and observations, with the last column of "ICU" being 1 for Yes or 0 for No. The task is to predict whether a patient will be admitted to ICU based on known data.

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Whats NLP Stands For?

NLP stands for Natural Language Processing which is a field of Artificial Intelligence with a lot of complexity and
techniques to in short words "understand what are you talking about".

And FHIR is...???

FHIR stands for Fast Healthcare Interoperability Resources and is a standard to data structures for healthcare. There are
some good articles here explainig better how FHIR interact with Intersystems IRIS.

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Keywords: IRIS, IntegratedML, Machine Learning, Covid-19, Kaggle

Continued from the previous Part I ... In part I, we walked through traditional ML approaches on this Covid-19 dataset on Kaggle.

In this Part II, let's run the same data & task, in its simplest possible form, through IRIS integratedML which is a nice & sleek SQL interface for backend AutoML options. It uses the same environment.

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