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1. The query topic (the training set) is defined by:
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The training set is a set of scientific articles related to the same topic. You can write a PubMed
query to build automatically a training set. Alternatively, you can use biomedical terms from the Medical Subject Headings (MeSH).
Please input only exact terms. These terms can be found in the
MeSH Browser or
hierarchical tree.
The procedure is detailed in the tutorial section.
The training set can be also defined with your own list of articles (identified by PubMed identifiers,
e.g. PMIDs). You can get a list of PMIDs in few clicks from the PubMed interface: go to the
Pubmed page, make a query, select 'UI List' in the Display
menu, and Send to file. Please see the related tutorial.
For demo: click on one of the following training set, and then on the 'Rank it' button:
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2. The reference (the background set) is defined by:
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The background set should use the whole medline database or a random selection of articles. You can also provide your own list to take into account a bias in
the test set.
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3. The abstracts to be ranked (the test set) are defined by:
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The test set defines abstracts which will be ranked by the MedlineRanker program. Ranking all the medline abstracts
of the last months or years may be long. The processing speed is approximately 1 Million abstracts (~2 years old abstracts) per minute after initialization steps.
The speed may vary depending on the server load.
Please cite:
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MedlineRanker: flexible ranking of biomedical literature.
Fontaine JF, Barbosa-Silva A, Schaefer M, Huska MR, Muro EM, Andrade-Navarro MA.
Nucleic Acids Research 2009 May 8; doi: 10.1093/nar/gkp353
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