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An Ontology-Based Knowledge Methodology in the Medical Domain in the Latin America: the Study Case of Republic of Panama

INTRODUCTION: Nowadays in Panama, there is a lot of patient information stored in textual form which cannot be manipulated to manage adequate knowledge. There are multiple resources created to represent knowledge, including specialized glossaries, ontologies, among others. The ontologies are an impo...

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Autores principales: Cedeno-Moreno, Denis, Vargas-Lombardo, Miguel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Academy of Medical sciences 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6029915/
https://www.ncbi.nlm.nih.gov/pubmed/30061779
http://dx.doi.org/10.5455/aim.2018.26.98-101
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author Cedeno-Moreno, Denis
Vargas-Lombardo, Miguel
author_facet Cedeno-Moreno, Denis
Vargas-Lombardo, Miguel
author_sort Cedeno-Moreno, Denis
collection PubMed
description INTRODUCTION: Nowadays in Panama, there is a lot of patient information stored in textual form which cannot be manipulated to manage adequate knowledge. There are multiple resources created to represent knowledge, including specialized glossaries, ontologies, among others. The ontologies are an important part within the scope of the recovery and organization of the information and the semantic web. Also in recent works they are used in applications of natural language processing (NLP), as a knowledge base. AIM: This research was conducted with the aim of creating a methodology that allows from a text written in NL, extract the necessary elements using NLP tools and with them create a knowledge base represented by one domain ontology and extract knowledge to help medical specialists. MATERIAL AND METHODS: In this study we carried out a methodology that allows the extraction of knowledge of patient clinical records, general medicine and palliative care, in order to show relevant knowledge elements to specialists. The methodology was validated with a data corpus of approximately 200 patient records. CONCLUSION: We have created a knowledge representation methodology, combining NLP techniques and tools and the automatic instantiation of an ontology, which can serve as a software agent for other applications or used to visualize the patient’s clinical information. The study was validated using the traditional metrics of information retrieval systems precision, recall, F-measure obtaining excellent results, and can be used as a software agent or methodology for the development of information extraction software systems in the medical domain.
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spelling pubmed-60299152018-07-30 An Ontology-Based Knowledge Methodology in the Medical Domain in the Latin America: the Study Case of Republic of Panama Cedeno-Moreno, Denis Vargas-Lombardo, Miguel Acta Inform Med Original Paper INTRODUCTION: Nowadays in Panama, there is a lot of patient information stored in textual form which cannot be manipulated to manage adequate knowledge. There are multiple resources created to represent knowledge, including specialized glossaries, ontologies, among others. The ontologies are an important part within the scope of the recovery and organization of the information and the semantic web. Also in recent works they are used in applications of natural language processing (NLP), as a knowledge base. AIM: This research was conducted with the aim of creating a methodology that allows from a text written in NL, extract the necessary elements using NLP tools and with them create a knowledge base represented by one domain ontology and extract knowledge to help medical specialists. MATERIAL AND METHODS: In this study we carried out a methodology that allows the extraction of knowledge of patient clinical records, general medicine and palliative care, in order to show relevant knowledge elements to specialists. The methodology was validated with a data corpus of approximately 200 patient records. CONCLUSION: We have created a knowledge representation methodology, combining NLP techniques and tools and the automatic instantiation of an ontology, which can serve as a software agent for other applications or used to visualize the patient’s clinical information. The study was validated using the traditional metrics of information retrieval systems precision, recall, F-measure obtaining excellent results, and can be used as a software agent or methodology for the development of information extraction software systems in the medical domain. Academy of Medical sciences 2018-06 /pmc/articles/PMC6029915/ /pubmed/30061779 http://dx.doi.org/10.5455/aim.2018.26.98-101 Text en © 2018 Denis Cedeno-Moreno, Miguel Vargas-Lombardo http://creativecommons.org/licenses/by-nc/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Paper
Cedeno-Moreno, Denis
Vargas-Lombardo, Miguel
An Ontology-Based Knowledge Methodology in the Medical Domain in the Latin America: the Study Case of Republic of Panama
title An Ontology-Based Knowledge Methodology in the Medical Domain in the Latin America: the Study Case of Republic of Panama
title_full An Ontology-Based Knowledge Methodology in the Medical Domain in the Latin America: the Study Case of Republic of Panama
title_fullStr An Ontology-Based Knowledge Methodology in the Medical Domain in the Latin America: the Study Case of Republic of Panama
title_full_unstemmed An Ontology-Based Knowledge Methodology in the Medical Domain in the Latin America: the Study Case of Republic of Panama
title_short An Ontology-Based Knowledge Methodology in the Medical Domain in the Latin America: the Study Case of Republic of Panama
title_sort ontology-based knowledge methodology in the medical domain in the latin america: the study case of republic of panama
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6029915/
https://www.ncbi.nlm.nih.gov/pubmed/30061779
http://dx.doi.org/10.5455/aim.2018.26.98-101
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