Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Learning to recognize phenotype candidates in the auto-immune literature using SVM re-ranking.

PloS one - 1 Jan 2013

Collier Nigel, Tran Mai-vu, Le Hoang-quynh, Ha Quang-Thuy, Oellrich Anika, Rebholz-Schuhmann Dietrich

Abstract excerpt

The identification of phenotype descriptions in the scientific literature, case reports and patient records is a rewarding task for bio-medical text mining. Any progress will support knowledge discovery and linkage to other resources. However because of their wide variation a number of challenges still remain in terms of their identification and semantic normalisation before they can be fully exploited for...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Artificial Intelligence
Share to Autoimmune Diseases

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Data Mining

Share to Entropy

Share to Models, Theoretical

Share to Semantics

Share to Support Vector Machine

Share to Vocabulary, Controlled

Source

Open in PubMed Open full text

Identifiers

PMID: 24155869
DOI: 10.1371/journal.pone.0072965
PMCID: PMC3796529

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 5 Sept 2026. Manifest publication-graph-cohort-2026-09-05.1.

Source receipt: pubmed, retrieved 5 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Learning to recognize phenotype candidates in the auto-immune literature using SVM re-ranking.PMID 24155869Read ↗

PPPred: Classifying Protein-phenotype Co-mentions Extracted from Biomedical LiteratureSemantic proximity Read ↗

Identifying Human Phenotype Terms by Combining Machine Learning and Validation Rules.Semantic proximity Read ↗

Automatic concept recognition using the human phenotype ontology reference and test suite corpora.Semantic proximity Read ↗

Challenges of Ontology-Based Concept Normalization for Deep Phenotyping in Rare Skin Diseases.Semantic proximity Read ↗

Darling: A Web Application for Detecting Disease-Related Biomedical Entity Associations with Literature Mining.Semantic proximity Read ↗

Thematic issue of the Second combined Bio-ontologies and Phenotypes Workshop.Semantic proximity Read ↗

A re-evaluation of biomedical named entity-term relations.Semantic proximity Read ↗

Investigation of synonym expansion and self-alignment pretraining for enhancing Human Phenotype Ontology concept recognition.Semantic proximity Read ↗

Discovery of novel biomarkers and phenotypes by semantic technologies.Semantic proximity Read ↗

A new synonym-substitution method to enrich the human phenotype ontology.Semantic proximity Read ↗

Mapping Phenotypic Information in Heterogeneous Textual Sources to a Domain-Specific Terminological Resource.Semantic proximity Read ↗

Integration of Annotated Phenotype, Gene and Chemical Text Data to Advance Exposome Informatics.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.