ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2008
A fast document classification algorithm for gene symbol disambiguation in the BITOLA literature-based discovery support system.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Networks of neuroinjury semantic predications to identify biomarkers for mild traumatic brain injury.Journal of biomedical semantics · 2015Article
- A literature search tool for intelligent extraction of disease-associated genes.Journal of the American Medical Informatics Association : JAMIAArticle
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Authors and funding
2 authors.
Funding
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Abstract
Gene symbol disambiguation is an important problem for biomedical text mining systems. When detecting gene symbols in MEDLINE citations one of the biggest challenges is the fact that many gene symbols also denote other, more general biomedical concepts (e.g. CT, MR). Our approach to this problem is first to classify the citations into genetic and non-genetic domains and then to detect gene symbols only in the genetic domain. We used ontological information provided by Medical Subject Headings (MeSH) for this classification task. The proposed algorithm is fast and is able to process the full MEDLINE distribution in a few hours. It achieves predictive accuracy of 0.91. The algorithm is currently implemented in the BITOLA literature-based discovery support system (http://www.mf.uni-lj.si/bitola/).
Indexed as
Identifiers
18998999PMC2655979What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.