Ethical and policy considerations in iHelp
The iHelp consortium is building an ambitious and far-reaching study using several inter-connected approaches to contribute to more effective risk detection and
Read MoreData ingestion pipelines (Part II)
In our previous blog, we presented an overview of how the data ingestion pipelines of the iHelp platform have been implemented. We
Read MoreData Ingestion into the iHelp Big Data Platform (Part I)
One of the most important technological building blocks of the iHelp platform is the data pipeline that captures the various types of
Read MoreBuilding the iHelp Platform
The modern healthcare landscape and market As the healthcare domain continues to become more complex with a tremendous amount of data being
Read MoreRisk Factor Analysis
Over the past few years, the incidence of pancreatic cancer (PC) has enlarged and AI techniques have emerged as powerful tools in
Read MoreGoals of the iHelp study: the FPG pilot
The main goals of the iHelp project are to early detect and mitigate the risks associated with Pancreatic Cancer by applying advanced
Read MoreUnsupervised Machine Learning
Have you met that know-it-all expert always rushing to spoil the AI party by pronouncing that they have seen it all before
Read MoreDigital Twins
The concept of Digital Twins was designed in 2002 by Michael Grieves [1], initially, to serve as a tool in the Product
Read MoreThe Open-Source in eHealth – The iHelp Solution
Since the project has moved to its third and final year it is time to have a small recap of the project’s
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