Skip main navigation

New offer! Get 30% off your first 2 months of Unlimited Monthly. Start your subscription for just £35.99 £24.99. New subscribers only T&Cs apply

Find out more

Home / Healthcare & Medicine / AI & Robotics / AI and Big Data in Global Health Improvement / Feeder-Net Fereated E-health Big Data for Evidence Renovation Network

Feeder-Net Fereated E-health Big Data for Evidence Renovation Network

video
View transcript
14.4
Okay, I’m also reading a research project provide in Korea, named the Feeder-Net Fereated E-health big data for evidence renovation network. Okay, this is a request for proposal of the government. The grant is 10 billion US dollar and three this is a three-year project. Here.
41.4
Here, in this project, we try to convert hospitals email data in term of CDM. Also we try to make a platform utilizing that hospital data without sharing the data. Just we want to share the evidence using the platform. Okay, here now 41 largest hospital in Korea joined in this project. So you can see nearly all biggest hospital in Korea, in Seoul area, these are big hospitals. Incheon, Gyeonggi, Chungcheong, Gangwon, Jeolla, Gyeongsang. Here, so by converting the hospitals… so we could convert hospital data into CDM. And it will include the patient data, 55 million patient data. There are some duplication because we do not link the patient data. So each hospital data are separated each other.
100
So in Korean, population only 51 million, but this data can be bigger than our population. We also will develop 7 extension model models and now seven companies join our conservation. So we make the feeder-net platform utilizing all of the data. So now, big companies join here, Evidnet, and SK is sort of the biggest company in Korea. They joined it here. And P-HIS company and Kobic company and AI company and other research institutes also joined our conversion. This is how Feeder-Net works. Feeder Node exists in each hospital. It is separated. So. And Portal, in the cloud… Here. okay.
169
Here researcher as the user of the platform can submit his research Python here, and then another company or researchers or anyone it can make analytic code the for the researchers and then analytic coders are distributed to 41 hospitals. And in the hospital, each Hospital decide whether to join or join this research or not, it is their privilege. And if they decided to accept the research, then they are allowed to run that analytic code against the data in the hospital. Then, we can get a result within 2 hours, 4 hours, and 10 hours. Then that results are stand bare to the researchers as synchronous manner.
229.1
So after submitting his analytic code and then he wait some days and he can get the data that results from 41 Hospitals. This is how the Feeder-Net platform works This is another business platform, basically, our platform do not provide service. That means other companies who have their business model, then can join our platform and they can develop their software and plug in their software into our platform. And by using them, by using our platform they can access all the patient data without considering any health information leakage or anything else. So this is an example of the overall the business model.
285.5
Some companies tried to integrate their genomic data with the hospitals to see each other’s data for the service of chronic disease care service, and perinatal mother service. Another company try to use this kind of data for the personalized chemotherapy recommendation. Another company want to use this platform for the diet training exercise service to the patient’s food decide discharged from the hospital. Okay, this is some other example of the business model. So this platform is open to anyone to any of you can join to our platform to share our data.

Dr. Rae Woong Park introduces another research project provide in Korea, named the Feeder-Net Fereated E-health big data for evidence renovation network.

In this study, 41 largest hospitals in Korea joined in this project. They converted hospitals’ data in terms of the Common Data Model and they use this platform utilizing hospital data. Around 55 million patient data is included in this platform. Each hospital data are separated from each other.

In addition, 7 extension model models were developed and now more companies have joined this project. This means the feeder-net platform can utilize all of the data once they participate. This is convenient for the researcher to gain the data as synchronous manner.

In the final part, Dr. Rae Woong Park explains a certain example of the business model. Like chronic disease care service, and perinatal mother service. Companies want to use data for personalized chemotherapy recommendation or diet training exercise service. etc.

Want to keep
learning?

This content is taken from
Taipei Medical University online course,

AI and Big Data in Global Health Improvement

View Course

Based on what we have heard of all the AI on healthcare, would you be able to come up with some idea of other possible solutions using Big Data to improve a certain disease treatment? Feel free to share any idea.

Want to keep learning?

This content is taken from Taipei Medical University online course
AI and Big Data in Global Health Improvement
View Course
See other articles from this course
This article is from the online course:

AI and Big Data in Global Health Improvement

Created by
Join Now
This article is from the free online

AI and Big Data in Global Health Improvement

Created by
Join Now
FutureLearn - Learning For Life

Reach your personal and professional goals

Unlock access to hundreds of expert online courses and degrees from top universities and educators to gain accredited qualifications and professional CV-building certificates.

Join over 18 million learners to launch, switch or build upon your career, all at your own pace, across a wide range of topic areas.

Start Learning now

Register to receive updates

  • Create an account to receive our newsletter, course recommendations and promotions.

    Register for free