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#IntegratedML

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InterSystems IntegratedML is an all-SQL machine learning (ML) module for InterSystems IRIS or IRIS for Health that:
- Gives users the ability to create, train and deploy powerful models from simple SQL syntax without requiring data scientists.
- Wraps "best of breed" open source and proprietary "AutoML" frameworks including DataRobot.
- Focuses on easy deployment to IRIS, so you can easily add machine learning to your applications.

Please find more information including videos and infographics at the IntegratedML Resource Guide.

Welcome dear members of the Community to the presentation and first article of a small project that will demonstrate the capabilities of InterSystems IRIS to provide full backup functionality for a web application developed in Angular. This article will be limited to presenting the concept as well as the InterSystems IRIS functionalities used in a general way, going into more detail in subsequent articles.

Welcome to QuinielaML!

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Article
· Jul 4, 2023 2m read
IntegratedMLandDashboardSample

A simple data analysis example created in IntegratedML and Dashboard

Based on InterSystems' Integrated ML technology and Dashboard, automatically generate relevant predictions and BI pages based on uploaded CSV files. The front and back ends are completed in Vue and Iris, allowing users to generate their desired data prediction and analysis pages with simple operations and make decisions based on them.

# ZPM installation

zpm:USER>install IntegratedMLandDashboardSample

# Process Deployment

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If you are a customer of the new InterSystems IRIS® Cloud SQL and InterSystems IRIS® Cloud IntegratedML® cloud offerings and want access to the metrics of your deployments and send them to your own Observability platform, here is a quick and dirty way to get it done by sending the metrics to Google Cloud Platform Monitoring (formerly StackDriver).

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Prediction of server configuration for entry

The platform server entry configuration prediction application connects to Iris in Java and uses its Integrated ML technology to analyze data such as hospital outpatient volume, number of services, number of messages, and message save time. It can predict the server configuration required for the hospital entry platform before the hospital integration platform enters, providing convenience for customers.

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· Jan 28 3m read
Fhir-HepatitisC-Predict

Processing FHIR resources with FHIR SQL BUILDER to predict the probability of developing hepatitis C disease

With the development of technology, the medical industry is also constantly advancing, and humans often pay more attention to their own health,
By learning and processing datasets through computers, diseases can be predicted.

Pre condition: Ability to use FHIR and ML
Firstly, our dataset is obtained from kaggle and transformed into FHIR resources based on patient gender, age, ALP or ALT, and imported into the FHIR resource repository

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Hi Community

This document mainly enriches the content of the previous article and introduces the use of the application.

Perhaps you have already read the previous article, but I still want to say,
After completing the initialization operation (including model creation and training), the Fhir HepatitisC Predict application then predicts HepatitisC

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