Open AccessDesign of a Rule Based Bio Medical Entity Extractor
Author(s) -
G. Suganya,
R Porkodi
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.e1055.0785s319
Subject(s) - computer science , biomedical text mining , extractor , named entity recognition , preprocessor , identification (biology) , artificial intelligence , information retrieval , natural language processing , named entity , annotation , field (mathematics) , information extraction , text mining , botany , management , process engineering , engineering , economics , biology , task (project management) , mathematics , pure mathematics
The field of Biomedical Entity Extraction/ Identification plays a vital role in Bioinformatics and rapidly growing to meet the needs of different text mining tasks. Many biomedical entity extraction tools have been developed so far. This research work has focused to develop a Rule based Biomedical Entity Extraction and tested with PubMed Medline abstracts of Colon cancer and Alzheimer disease categories. The proposed Biomedical Entity Extractor gives promising result when compared with existing tools. The proposed method is incorporating of two phases such as preprocessing the input text document using NLP techniques and create the rules to find out the biomedical entities using regular expression. The results of Rule based Biomedical Entity Extractor are validated with the well-known Biomedical Genia tagger and Genecards Database. The method proposed in this paper almost good as genia tagger. The evaluation results on Colon cancer and Alzheimer disease abstracts corpus of Biomedical Entity Extraction achieve an accuracy of 92% and 88% respectively which identifies more number of entities compared to other existing tools.