Named entity recognition and relation detection for biomedical information extraction

N Perera, M Dehmer, F Emmert-Streib - Frontiers in cell and …, 2020 - frontiersin.org
The number of scientific publications in the literature is steadily growing, containing our
knowledge in the biomedical, health, and clinical sciences. Since there is currently no …

Deep learning methods for biomedical named entity recognition: a survey and qualitative comparison

B Song, F Li, Y Liu, X Zeng - Briefings in Bioinformatics, 2021 - academic.oup.com
The biomedical literature is growing rapidly, and the extraction of meaningful information
from the large amount of literature is increasingly important. Biomedical named entity …

[HTML][HTML] NCBI disease corpus: a resource for disease name recognition and concept normalization

RI Doğan, R Leaman, Z Lu - Journal of biomedical informatics, 2014 - Elsevier
Abstract Information encoded in natural language in biomedical literature publications is
only useful if efficient and reliable ways of accessing and analyzing that information are …

[PDF][PDF] Overview of BioNLP'09 shared task on event extraction

JD Kim, T Ohta, S Pyysalo, Y Kano… - Proceedings of the …, 2009 - aclanthology.org
The paper presents the design and implementation of the BioNLP'09 Shared Task, and
reports the final results with analysis. The shared task consists of three sub-tasks, each of …

Literature mining for the biologist: from information retrieval to biological discovery

LJ Jensen, J Saric, P Bork - Nature reviews genetics, 2006 - nature.com
For the average biologist, hands-on literature mining currently means a keyword search in
PubMed. However, methods for extracting biomedical facts from the scientific literature have …

Overview of BioCreative II gene mention recognition

L Smith, LK Tanabe, RJ Ando, CJ Kuo, IF Chung… - Genome biology, 2008 - Springer
Nineteen teams presented results for the Gene Mention Task at the BioCreative II Workshop.
In this task participants designed systems to identify substrings in sentences corresponding …

Overview of BioCreAtIvE: critical assessment of information extraction for biology

L Hirschman, A Yeh, C Blaschke, A Valencia - BMC bioinformatics, 2005 - Springer
Background The goal of the first BioCreAtIvE challenge (Critical Assessment of Information
Extraction in Biology) was to provide a set of common evaluation tasks to assess the state of …

[HTML][HTML] Biomedical text mining and its applications in cancer research

F Zhu, P Patumcharoenpol, C Zhang, Y Yang… - Journal of biomedical …, 2013 - Elsevier
Cancer is a malignant disease that has caused millions of human deaths. Its study has a
long history of well over 100years. There have been an enormous number of publications on …

CHEMDNER: The drugs and chemical names extraction challenge

M Krallinger, F Leitner, O Rabal, M Vazquez… - Journal of …, 2015 - Springer
Natural language processing (NLP) and text mining technologies for the chemical domain
(ChemNLP or chemical text mining) are key to improve the access and integration of …

Concept annotation in the CRAFT corpus

M Bada, M Eckert, D Evans, K Garcia, K Shipley… - BMC …, 2012 - Springer
Background Manually annotated corpora are critical for the training and evaluation of
automated methods to identify concepts in biomedical text. Results This paper presents the …