ArticleData integration in the life sciences : ... International Workshop, DILS ... : proceedings. DILS (Conference)2015
GEM: The GAAIN Entity Mapper.
Article in Data integration in the life sciences : ... International Workshop, DILS ... : proceedings. DILS (Conference), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Yeast culture promotes butyrate produced fibrolytic bacteria as intracellular hydrogen sink in the rumen.Microbiome · 2026Article
- The GAAIN Entity Mapper: An Active-Learning System for Medical Data Mapping.Frontiers in neuroinformatics · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
We present a software system solution that significantly simplifies data sharing of medical data. This system, called GEM (for the GAAIN Entity Mapper), harmonizes medical data. Harmonization is the process of unifying information across multiple disparate datasets needed to share and aggregate medical data. Specifically, our system automates the task of finding corresponding elements across different independently created (medical) datasets of related data. We present our overall approach, detailed technical architecture, and experimental evaluations demonstrating the effectiveness of our approach.
Identifiers
What 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.