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Docker InterSystems Extension

Docker Extension for InterSystems

Dmitry Maslennikov
Docker
5.0 (5)20 Sep, 2022 998

GraphQL

GraphQL provides a complete and understandable description of the data in your API, gives clients the power to ask for exactly what they need and nothing more, makes it easier to evolve APIs over time, and enables powerful developer tools.

G
Gevorg Arutiunian
Docker
0.0 (0)16 Sep, 2022 677

InterSystems Ideas Waiting to be Implemented

RPMShare - Database solution for remote patient monitoring (RPM) datasets of high density vitals

Why Currently, patient home monitoring is a megatrend, promising to reduce readmission, and emergency visits and globally add years of health. Owing to US 21st Century act and Reimbursement Schedule from Medicare (up to 54 USD per month per patient) US market is flooded with RPM companies (over 100 for sure) providing primary physicians and hospitals the possibility to collect data from patients' homes, including blood pressure, blood sugar, weight, heart rate, and others. Most companies collect and store the data in free formats, creating an "unholy mess" of data, which has a very limited chance to be ever reused. The hospital only gets insights from single patient results as a dashboard concentrating on cases showing vitals going out of normal range. While research by scientific groups and several advanced companies shows that even data of medium accuracy could predict adverse events like heart failure weeks before happening. A project which is able to provide a federated environment for these new types of data, allowing patients and hospitals truly own data, connecting it to classic EHR, and making data readily available for AI/ML, a project like this is poised to conquer the US maket, with other markets following the trend. Who RPM Companies collecting the data will love the solution which will transfer the data from devices using FHIR, provide full security and compliance, and will include a multitude of routine functions for data analysis, and even data representation. They will stop creating hundreds of repositories of similar software code and concentrate on patient success. Hospitals will be able to have their own structured and standardized silos of data, they will have a chance to change RPM providers, and have a history of patient vitals. They will have EHR data and RPM data connected. Dashboards could be integrated into existing EMRs much easier and finally, they will be precious sources of integrated data for research. Patients will be able to reuse their data, have it analyzed by leading health tech companies, and enrich their vitals with even more data from wearables and other devices. Researchers will be able to analyze the data in the same cloud as it is stored, and by anonymizing datasets, with integrated EMR and RPM data, they could potentially assemble unprecedented volumes of data. AI/ML-ready datasets will boost the predictive power of digital health in only a few years from the first implementations of data collection. How HealthShare is already able to store and receive data in FHIR format, minor additions for hl7 standards are to be implemented and accepted by the community. In a way, RPMshare is a mini-version of HealthShare, if designed using an interoperability framework it could even have universal connection standards for existing devices. A secret sauce could be made from the integration of InterSystems solutions in anonymization and the IntegratedML package with RPMshare. To create immediate value and populate cloud service a consortium or partnership with existing RPM companies could be developed, where they will receive benefits of instrumentation and standardization and InterSystems will populate hundreds of thousands of years of observations (assuming companies already have tens of thousands of clients). In simple words, it is an Uber for RPM data.

D
by Dmitry Alexeev

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n8n-nodes-iris

Support for InterSystems IRIS in an automation platform n8n

Dmitry Maslennikov
Docker
IPM
5.0 (1)15 Sep, 2022 465

Digistat Connect

Multiple medical devices. One solution to harvest their data.

S
Sabri Romdhani
0.0 (0)15 Sep, 2022 259

Digistat Smart Central

Enhancing visibility of patient conditions

S
Sabri Romdhani
0.0 (0)15 Sep, 2022 360

The Ascom Myco 3 smartphone

The Myco 3 makes information accessible to clinicians

S
Sabri Romdhani
0.0 (0)15 Sep, 2022 307

interoperability-test

Unit Test Interoperability production interface

O
Oliver Wilms
Docker
IPM
5.0 (1)15 Sep, 2022 329 10

interoperability-soap

Tool to help troubleshoot Generic SOAP Service interface

O
Oliver Wilms
Docker
IPM
5.0 (1)15 Sep, 2022 192 2

demo-deployment

Deploy Demo of your InterSystems IRIS application

Dmitry Maslennikov
5.0 (1)14 Sep, 2022 210

samba-iris-adapter

InterSystems IRIS Support to Samba protocol (smb v2/v3)

Yuri Marx
Docker
IPM
5.0 (1)14 Sep, 2022 404 10

Sustainable Machine Learning

Sustainable Machine Learning for the InterSystems contest

L
Lucas Enard
Docker
Python
IPM
4.5 (1)11 Sep, 2022 462 10

production-monitor

Custom Production Monitor

O
Oliver Wilms
Docker
IPM
5.0 (1)11 Sep, 2022 404 17

appmsw-banks-ru

An example of working with the service for updating the list of Russian banks

Sergey Mikhailenko
Docker
IPM
5.0 (1)11 Sep, 2022 157 5

Community objectscriptQuality

ObjectScript code analysis for community projects

D
Daniel
IPM
4.0 (1)08 Sep, 2022 413

DC Analytics

InterSystems Developer Community analytics.

E
Evgeniy Potapov
Docker
IPM
4.5 (2)06 Sep, 2022 648

PMML Business Operation

With this simple Business Operation, you can easily leverage your predictive models (saved as PMML) in a Production. There's both a generic BO and a utility method that allows you to generate dedicated operation / request / response classes.

B
Benjamin De Boe
ML
ML
0.0 (0)31 Aug, 2022 327

iris-readonly-interop

Read Only Role for Interoperability

G
Guillaume Rongier
Docker
IPM
5.0 (2)30 Aug, 2022 420 58

iris-fine-tuned-ml

Train and tune a machine learning model using IRIS and Python

L
Lucas Enard
Docker
Python
ML
ML
4.0 (1)24 Aug, 2022 289

iris-web-scraping

Simple web scraping using full Python in IRIS

L
Lucas Enard
Docker
Python
4.5 (1)24 Aug, 2022 263

Data Catalog

A single solution to easily discover and access reliable data

P
Paulo Taylor
0.0 (0)24 Aug, 2022 304

SETI Viewer

Add-on to unlock the Clinical Viewer feature of SETI.

L
Louis Kabelka
IPM
0.0 (0)18 Aug, 2022 248 17

SETI

Extends SDA and propagates to Health Insight & Clinical Viewer.

L
Louis Kabelka
IPM
5.0 (1)18 Aug, 2022 504 29

iris-python-flask-api-template

The simplest template with REST CRUD for InterSystems IRIS

L
Lucas Enard
Docker
Python
4.5 (1)17 Aug, 2022 405

fhir-orga-dt

This is a simple full python IRIS production that gather information from a csv, use a DataTransformation to make it into a FHIR object and then, save that information to a FHIR server.

L
Lucas Enard
Docker
Python
4.5 (1)17 Aug, 2022 316

formation-template-python

Formation to learn InterSystems' interoperability framework using python

L
Lucas Enard
Docker
Python
5.0 (1)17 Aug, 2022 519

UnitTest_DTL_HL7

HL7 DTL TestCase Creator and Runner Framework

A
Alex Woodhead
0.0 (0)15 Aug, 2022 329

CoffeeCo Full Stack Tutorial

IRIS Coffee Company tutorial

R
Raj Singh
Python
3.0 (1)12 Aug, 2022 298

atscale-backups

AtScale backup tool

E
Evgeniy Potapov
Docker
Python
IPM
0.0 (0)12 Aug, 2022 180 6

iris-local-ml

How to use Python and IRIS to run Machine learnings algorithms

L
Lucas Enard
Docker
Python
AI
ML
ML
4.0 (1)02 Aug, 2022 399

iris-fix-protocol

Integration of the FIX protocol inside IRIS using Python

L
Lucas Enard
Docker
Python
0.0 (0)28 Jul, 2022 303