TY - GEN
T1 - Knowledge extraction and mining in biomedical research using rule network model
AU - Chan, S. W.
AU - Leung, C. H.C.
AU - Milani, A.
N1 - Copyright:
Copyright 2014 Elsevier B.V., All rights reserved.
PY - 2013
Y1 - 2013
N2 - Recent findings show that the quantity of published biomedical literature is increasing at a dramatic rate. Carrying out knowledge extraction from large amounts of research literature becomes a significant challenge. Here we introduce an automatic mechanism for processing such information and extracting meaningful medical knowledge from biomedical literature. Data mining and natural language processing (NLP) are applied in a novel model, called biomedical rule network model. Using this model, information and relationships among herbal materials and diseases, as well as the chemical constituents of herbs can be extracted automatically. Moreover, with the overlapping chemical constituents of herbs, alternative herbal materials can be discovered, and suggestions can be made to replace expensive treatment options with lower cost ones.
AB - Recent findings show that the quantity of published biomedical literature is increasing at a dramatic rate. Carrying out knowledge extraction from large amounts of research literature becomes a significant challenge. Here we introduce an automatic mechanism for processing such information and extracting meaningful medical knowledge from biomedical literature. Data mining and natural language processing (NLP) are applied in a novel model, called biomedical rule network model. Using this model, information and relationships among herbal materials and diseases, as well as the chemical constituents of herbs can be extracted automatically. Moreover, with the overlapping chemical constituents of herbs, alternative herbal materials can be discovered, and suggestions can be made to replace expensive treatment options with lower cost ones.
KW - Biomedical literature
KW - Chemical constituent
KW - Herb
KW - Hypothesis
KW - Natural language processing
UR - http://www.scopus.com/inward/record.url?scp=84892926295&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-02753-1_51
DO - 10.1007/978-3-319-02753-1_51
M3 - Conference proceeding
AN - SCOPUS:84892926295
SN - 9783319027524
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 506
EP - 515
BT - Brain and Health Informatics - International Conference, BHI 2013, Proceedings
T2 - International Conference on Brain and Health Informatics, BHI 2013
Y2 - 29 October 2013 through 31 October 2013
ER -