Using an Ontological Representation of Chemotherapy Toxicities for Guiding Information Extraction and Integration from EHRs.
Stud Health Technol Inform
; 290: 91-95, 2022 Jun 06.
Article
en En
| MEDLINE
| ID: mdl-35672977
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.Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Efectos Colaterales y Reacciones Adversas Relacionados con Medicamentos
/
Neoplasias
Tipo de estudio:
Prognostic_studies
/
Qualitative_research
Límite:
Humans
Idioma:
En
Revista:
Stud Health Technol Inform
Asunto de la revista:
INFORMATICA MEDICA
/
PESQUISA EM SERVICOS DE SAUDE
Año:
2022
Tipo del documento:
Article
País de afiliación:
Francia