Lung Cancer Diagnosis Extraction from Clinical Notes Written in Spanish

The wide adoption of electronic health records (EHRs) offers a potential source to support research. Lung cancer is one of the most common cancer in the world. Although several tools have been developed to automatically extract concepts from oncology clinical notes, still there is a gap between conc...

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Bibliographic Details
Main Authors: Solarte-Pabon, Oswaldo, Torrente, Maria, Rodriguez-Gonzalez, Alejandro, Provencio, Mariano, Menasalvas, Ernestina, Tunas, Juan Manuel
Format: Conference Proceeding
Language:English
Subjects:
Cancer
Data mining
Diagnosis extraction
Information Extraction
Lung
Lung cancer Diagnosis
Medical diagnostic imaging
Natural language processing
Natural Language Processing (NLP)
Neoplasms
Online Access:Request full text
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Summary:The wide adoption of electronic health records (EHRs) offers a potential source to support research. Lung cancer is one of the most common cancer in the world. Although several tools have been developed to automatically extract concepts from oncology clinical notes, still there is a gap between concept extraction and concept understanding. The high number of clinical notes for the same patient, use of negation and proper date annotations lays in the root of the problem. In this paper, we propose an approach to accurate Lung cancer diagnosis extraction from clinical notes written in Spanish. The approach deals with a disambiguation process required to extract the correct date and diagnosis of a patient having hundreds of clinical notes and consequently hundreds of annotations. Results obtained on an annotated database of 1000 patients show an F-score of 90%.
ISSN:2372-9198
DOI:10.1109/CBMS49503.2020.00099