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Data Lakehouse to support the development of AI models for predicting patient clinical response to targeted and immuno-therapies

Authors: Coquelet Elodine; Marta, Silva; Balbi Laura; Riba Jofre; Alfaro Javier; Zanzotto Fabio Massimo; Pesquita Catia; +2 Authors

Data Lakehouse to support the development of AI models for predicting patient clinical response to targeted and immuno-therapies

Abstract

In the context of the European project KATY on precision medicine, we prototyped a Data Lakehouse by integrating research studies that generated molecular profiling data from cohorts of kidney tumor tissues taken from patients included in drug clinical trials. Indeed, there is currently a lack of a database dedicated to support the development of AI models to help doctors in chosing the best drug for each patient. The Data Lakehouse architecture, which we have implemented with open source Delta Lake technology, brings together the best features of Data Lake and Data Warehouse. The Data Lakehouse will allow three types of access for the KATY consortium members: - the implementation of data analytics approaches to query and visualize molecular and clinical data - the targeted extraction of data for the training and testing of AI models - feeding a Knowledge Graph to support the explainability of the predictive models using a priori biological and clinical knowledge.

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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