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
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Data 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
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Data 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
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Building 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
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Risk Factor Analysis
Over the past few years, the incidence of pancreatic cancer (PC) has enlarged and AI techniques have emerged as powerful tools in
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Goals 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
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Unsupervised 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
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Digital Twins
The concept of Digital Twins was designed in 2002 by Michael Grieves [1], initially, to serve as a tool in the Product
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The 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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