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#FHIR

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Fast Healthcare Interoperability Resources (FHIR, pronounced "fire") is a draft standard describing data formats and elements (known as "resources") and an application programming interface (API) for exchanging electronic health records

Official site

Overview

In our previous post, we discussed the motivation for developing a chatbot agent with access to FHIR resources. In this post, we will dive into the high-level design aspects of integrating a Streamlit-based chat interface with a Java SpringBoot backend, and enabling a LangChain agent with access to FHIR (Fast Healthcare Interoperability Resources) via APIs.

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Article
· Feb 1 2m read
Mind map your FHIR patient data

According Wikipedia a mind map is a diagram used to visually organize information into a hierarchy, showing relationships among pieces of the whole. It is often created around a single concept, drawn as an image in the center of a blank page, to which associated representations of ideas such as images, words and parts of words are added. Major ideas are connected directly to the central concept, and other ideas branch out from those major ideas.

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Article
· Jan 29 2m read
Get familiar with FHIR

🔥 Curious about the FHIR standard that everyone's talking about?

📚 Read on for a brief introduction, then try a brand-new learning path to get more in-depth knowledge!

The HL7® FHIR® standard has revolutionized the way healthcare developers take on the challenges of data interoperability. FHIR allows healthcare systems to exchange information seamlessly, and patient data can be consolidated in real time, regardless of where it's stored.

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I created this application considering how to convert images such as prescription forms into FHIR messages

It recognizes the text in the image through OCR technology and extracts it, which is then transformed into fhir messages through AI (LLA language model).

Finally, sending the message to the fhir server of IntereSystems can verify whether the message meets the fhir requirements. If approved, it can be viewed on the select page.

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Article
· 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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1、Background

When I first encountered FHIR, I encountered a problem with its message format. It was difficult for me to determine whether the message I created met the format, and it was also difficult to easily create an FHIR message from scratch.

So, through fhir server of IntereSystems’fhirserver API, I created this application for quickly generating/validating FHIR messages.

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