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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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creator | Solarte-Pabon, Oswaldo Torrente, Maria Rodriguez-Gonzalez, Alejandro Provencio, Mariano Menasalvas, Ernestina Tunas, Juan Manuel |
description | 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%. |
doi_str_mv | 10.1109/CBMS49503.2020.00099 |
format | conference_proceeding |
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language | eng |
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source | IEEE Xplore All Conference Series |
subjects | Cancer Data mining Diagnosis extraction Information Extraction Lung Lung cancer Diagnosis Medical diagnostic imaging Natural language processing Natural Language Processing (NLP) Neoplasms |
title | Lung Cancer Diagnosis Extraction from Clinical Notes Written in Spanish |
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