@inproceedings{44542134edf94cf8a12ed2c3f3f9fc32,
title = "Automatic extraction of HLA-disease interaction information from biomedical literature",
abstract = "The HLA control a variety of function involved in immune response and influence susceptibility to over 40 diseases. It is important to find out how HLA cause the disease or modify susceptibility or course of it. In this paper, we developed an automatic HLA-disease information extraction procedure that uses biomedical publications. First, HLA and diseases are recognized in the literature using built-in regular languages and disease categories of Mesh. Second, we generated parse trees for each sentence in PubMed using collins parser. Third, we build our own information extraction algorithm. The algorithm searched parsing trees and extracted relation information from sentences. We automatically collected 10,184 sentences from 66,785 PubMed abstracts using HaDextract. The precision rate of extracted relations reported 89.6% in randomly selected 144 sentences.",
keywords = "Disease, HLA, Interaction information, Textmining",
author = "Chae, {Jeong Min} and Chae, {Ji Eun} and Taemin Lee and Younghee Jung and Heungbum Oh and Soonyoung Jung",
year = "2009",
doi = "10.1007/978-3-642-10238-7_18",
language = "English",
isbn = "9783642102370",
series = "Communications in Computer and Information Science",
pages = "219--230",
editor = "Tai-hoon Kim and Yang, {Laurence T.} and Park, {Jong Hyuk} and Chang, {Alan Chin-Chen} and Thanos Vasilakos and Yan Zhang and Damien Sauveron and Xingang Wang and Young-Sik Jeong",
booktitle = "Advances in Computational Science and Engineering",
}