ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2017
Extracting geographic locations from the literature for virus phylogeography using supervised and distant supervision methods.
Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Patient-Related Metadata Reported in Sequencing Studies of SARS-CoV-2: Protocol for a Scoping Review and Bibliometric Analysis.JMIR research protocols · 2025Article
- Article
- Bi-directional Recurrent Neural Network Models for Geographic Location Extraction in Biomedical Literature.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2019Article
- Deep neural networks and distant supervision for geographic location mention extraction.Bioinformatics (Oxford, England) · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
The field of phylogeography allows researchers to model the spread and evolution of viral genetic sequences. Phylogeography plays a major role in infectious disease surveillance, viral epidemiology and vaccine design. When conducting viral phylogeographic studies, researchers require the location of the infected host of the virus, which is often present in public databases such as GenBank. However, the geographic metadata in most GenBank records is not precise enough for many phylogeographic studies; therefore, researchers often need to search the articles linked to the records for more information, which can be a tedious process. Here, we describe two approaches for automatically detecting geographic location mentions in articles pertaining to virus-related GenBank records: a supervised sequence labeling approach with innovative features and a distant-supervision approach with novel noise- reduction methods. Evaluated on a manually annotated gold standard, our supervised sequence labeling and distant supervision approaches attained F-scores of 0.81 and 0.66, respectively.
Identifiers
28815119PMC5543364What 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.