ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2012
Using SemRep to label semantic relations extracted from clinical text.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 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
16 citing papers in PubMed.
- Dynamic transcriptome landscape of pulmonary tissues of rats infected withAmerican journal of translational research · 2022Article
- Dynamic transcriptome landscape of Paragonimus proliferus developmental stages in the rat lungs.Parasitology research · 2021Article
- A Knowledge Graph of Combined Drug Therapies Using Semantic Predications From Biomedical Literature: Algorithm Development.JMIR medical informatics · 2020Article
- Integrating Unified Medical Language System and Kleinberg's Burst Detection Algorithm into Research Topics of Medications for Post-Traumatic Stress Disorder.Drug design, development and therapy · 2020Article
- BEERE: a web server for biomedical entity expansion, ranking and explorations.Nucleic acids research · 2019Article
- Article
- Exploiting semantic patterns over biomedical knowledge graphs for predicting treatment and causative relations.Journal of biomedical informatics · 2018Article
- SemaTyP: a knowledge graph based literature mining method for drug discovery.BMC bioinformatics · 2018Article
- Generalized Extraction and Classification of Span-Level Clinical Phrases.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2018Article
- Automatic Generation of Conditional Diagnostic Guidelines.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2016Article
- Ease of adoption of clinical natural language processing software: An evaluation of five systems.Journal of biomedical informatics · 2015Article
- Assessing the role of a medication-indication resource in the treatment relation extraction from clinical text.Journal of the American Medical Informatics Association : JAMIA · 2015Article
- Networks of neuroinjury semantic predications to identify biomarkers for mild traumatic brain injury.Journal of biomedical semantics · 2015Article
- SKIMMR: facilitating knowledge discovery in life sciences by machine-aided skim reading.PeerJ · 2014Article
- Learning to identify treatment relations in clinical text.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2014Article
- SemMedDB: a PubMed-scale repository of biomedical semantic predications.Bioinformatics (Oxford, England) · 2012Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
In this paper we examined the relationship between semantic relatedness among medical concepts found in clinical reports and biomedical literature. Our objective is to determine whether relations between medical concepts identified from Medline abstracts may be used to inform us as to the nature of the association between medical concepts that appear to be closely related based on their distribution in clinical reports. We used a corpus of 800k inpatient clinical notes as a source of data for determining the strength of association between medical concepts and SemRep database as a source of labeled relations extracted from Medline abstracts. The same pair of medical concepts may be found with more than one predicate type in the SemRep database but often with different frequencies. Our analysis shows that predicate type frequency information obtained from the SemRep database appears to be helpful for labeling semantic relations obtained with measures of semantic relatedness and similarity.
Indexed as
Identifiers
23304331PMC3540517What 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.