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Using an Ontological Representation of Chemotherapy Toxicities for Guiding Information Extraction and Integration from EHRs
Alice Rogier, Adrien Coulet, Bastien Rance
91 - 95
10.3233/SHTI220038
Research Article
Studies in Health Technology and Informatics
Volume 290: MEDINFO 2021: One World, One Health – Global Partnership for Digital Innovation
Abstract

Introduction:

Chemotherapies against cancers are often interrupted due to severe drug toxicities, reducing treatment opportunities. For this reason, the detection of toxicities and their severity from EHRs is of importance for many downstream applications. However toxicity information is dispersed in various sources in the EHRs, making its extraction challenging.

Methods:

We introduce OntoTox, an ontology designed to represent chemotherapy toxicities, its attributes and provenance. We illustrated the interest of OntoTox by integrating toxicities and grading information extracted from three heterogeneous sources: EHR questionnaires, semi-structured tables, and free-text.

Results:

We instantiated 53,510, 2,366 and 54,420 toxicities from questionnaires, tables and free-text respectively, and compared the complementarity and redundancy of the three sources.

Discussion:

We illustrated with this preliminary study the potential of OntoTox to guide the integration of multiple sources, and identified that the three sources are only moderately overlapping, stressing the need for a common representation.

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