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#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.

Hi Community!

Please welcome a new video on InterSystems Developers YouTube Channel:

Getting Sharded with InterSystems IRIS

https://www.youtube.com/embed/cEz_rJpsku0
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Here're the technology bonuses for the InterSystems IRIS Cloud SQL and IntegratedML Contest 2023 that will give you extra points in the voting:

  • IntegratedML usage
  • Online Demo
  • Article on Developer Community
  • The second article on Developer Community
  • Video on YouTube
  • First Time Contribution
  • Community Idea Implementation
  • IRIS Cloud SQL Survey

See the details below.<--break->

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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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Fun or No Fun - how serious is it?


Large language models are stirring up some phenomena in recent months. So inevitably I was playing ChatGPT too over last weekend, to probe whether it would be a complimentary to some BERT based "traditional" AI chatbots I was knocking up, or rather would it simply sweep them away.

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In our latest episode of Data Points, I had a conversation with @Thomas Dyar about AI Link, which helps bridge the gap between data scientists and business analysts. Our conversation talks about how AI Link fits with IntegratedML and Adaptive Analytics, as well, as what new features are on the horizon for IntegratedML. Take a listen!

https://5e18edf067eb59-03854285.castos.com/player/1346398
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Hello everyone, this is with great pleasure that I announce the V2 of my application 'Contest-FHIR'.

In this new version, I used new tools and techniques I discovered at the EUROPEAN HEALTHCARE HACKATHON in which I was invited by InterSystems as a guest and as a mentor to display the multiple projects I did in my intership back in April 2022.

Today I present to you the V2 of my application, it can now transform CSV to FHIR to SQL to JUPYTER notebook.

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Discussion
· Sep 16, 2022
txt2img
Several models, such as DALL-E, Midjourney, and StableDiffusion, became available recently. All these models generate digital images from natural language descriptions. The most interesting one, in my opinion, is StableDiffusion which is open source - released barely a few weeks ago. There's now an entire community trying to leverage it for various use cases.
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In this article, I am trying to identify the multiple areas to develop the features we can able to do using python and machine learning.

Each hospital is every moment trying to improve its quality of service and efficiency using technology and services.

The healthcare sector is one of the very big and vast areas of service options available and python is one of the best technology for doing machine learning.

In every hospital, humans will come with some feelings, if this feeling will understand using technology is make a chance to provide better service.

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Hey Community,

Don't miss the latest videos on InterSystems Developers YouTube channel:

⏯ IntegratedML Update from the Field

https://www.youtube.com/embed/2-i2Z7aukSc
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Maternal Risk can be measured from some parameters well known to the medical community. In this way, in order to help the medical community and computerized systems, especially AI, the scientist Yasir Hussein Shakir published a very useful dataset for training ML algorithms in the detection/prediction of Maternal Risk.

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Kidney Disease can be discovered from some parameters well known to the medical community. In this way, in order to help the medical community and computerized systems, especially AI, the scientist Akshay Singh published a very useful dataset for training ML algorithms in the detection/prediction of kidney disease. This publication can be found on the largest and best known data repository for ML, Kaggle at https://www.kaggle.com/datasets/akshayksingh/kidney-disease-dataset.

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Diabetes can be discovered from some parameters well known to the medical community. In this way, in order to help the medical community and computerized systems, especially AI, the National Institute of Diabetes and Digestive and Kidney Diseases published a very useful dataset for training ML algorithms in the detection/prediction of diabetes. This publication can be found on the largest and best known data repository for ML, Kaggle at https://www.kaggle.com/datasets/mathchi/diabetes-data-set.

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Hi Community,

Don't miss the new video on InterSystems Developers YouTube:

⏯ Exploring Machine Learning with R Language Gateway

https://www.youtube.com/embed/GcN2wD-3FnA
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Hey Community,

Enjoy watching the new video on InterSystems Developers YouTube channel:

⏯ Creating Virtual Models with InterSystems IRIS Adaptive Analytics

https://www.youtube.com/embed/E9jBHljk9To
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Hi Community,

Please welcome the new video from #VSummit20:

⏯ Showcasing Health Insight & IntegratedML for Healthcare Applications

https://www.youtube.com/embed/q8lC2a6eFgY
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Hi Community,

We're pleased to invite you to the online meetup with the winners of the InterSystems AI contest!

Date & Time: Friday, July 30, 2021 – 11:00 AM EDT

What awaits you at this Virtual Meetup?

  • Our winners' bios.
  • Short demos on their applications.
  • An open discussion about technologies being used. Q&A. Plans for the next contests.

https://www.youtube.com/embed/27vE9o9U3nM
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