Natural Language Processing Approaches for Retrieval of Clinically Relevant Genomic Information in Cancer.
Stud Health Technol Inform
; 295: 350-353, 2022 Jun 29.
Article
em En
| MEDLINE
| ID: mdl-35773881
ABSTRACT
The accelerating impact of genomic data in clinical decision-making has generated a paradigm shift from treatment based on the anatomic origin of the tumor to the incorporation of key genomic features to guide therapy. Assessing the clinical validity and utility of the genomic background of a patient's cancer represents one of the emerging challenges in oncology practice, demanding the development of automated platforms for extracting clinically relevant genomic information from medical texts. We developed PubMiner, a natural language processing tool to extract and interpret cancer type, therapy, and genomic information from biomedical abstracts. Our initial focus has been the retrieval of gene names, variants, and negations, where PubMiner performed highly in terms of total recall (91.7%) with a precision of 79.7%. Our next steps include developing a web-based interface to promote personalized treatment based on each tumor's unique genomic fingerprints.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Processamento de Linguagem Natural
/
Neoplasias
Tipo de estudo:
Prognostic_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2022
Tipo de documento:
Article