Detection and prediction of toxicity and response to chemotherapy from patient records



Main objectives

Detection and prediction of toxicity and response to chemotherapy treatment from patient records

The occurrence of adverse events and the response to chemotherapy treatment are two modalities of the same essential component to be analyzed in order to improve and personalize cancer treatment. Information on these events is mostly present in an indirect way within hospital data warehouses in biological results, chemotherapy follow-up data and reports. We wish to implement a tool for automatic detection of these types of events. This tool will consider both structured data and textual data via automatic language processing (ALP) techniques to extract the presence or not of toxicity and response. This first essential step will allow us to develop predictive models of toxicity.

This project is led by the HeKa team.

Contacts : Adrien Coulet (rf.ai1718627424rni@t1718627424eluoc1718627424.neir1718627424da1718627424); Bastien Rance (rf.ph1718627424pa@ec1718627424nar.n1718627424eitsa1718627424b1718627424)
François Marin/AP-HP



AP-HP, Inria, Inserm, Université de Paris

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Names of partners involved
AP-HP, Inria & Centrale Supélec

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