ReviewJournal of biomedical semantics2017
Semantic annotation in biomedicine: the current landscape.
Review in Journal of biomedical semantics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 2 of them syntheses that pooled it.
What it found
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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.
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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.
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Who cites it
27 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Natural language processing algorithms for mapping clinical text fragments onto ontology concepts: a systematic review and recommendations for future studies.Journal of biomedical semantics · 2020Pooled it
- Computational pathology definitions, best practices, and recommendations for regulatory guidance: a white paper from the Digital Pathology Association.The Journal of pathology · 2019Guideline
- Automating the extraction of otology symptoms from clinic letters: a methodological study using natural language processing.BMC medical informatics and decision making · 2025Article
- MetaTron: advancing biomedical annotation empowering relation annotation and collaboration.BMC bioinformatics · 2024Article
- Knowledge Graph Embeddings for ICU readmission prediction.BMC medical informatics and decision making · 2023Article
- A substring replacement approach for identifying missing IS-A relations in SNOMED CT.Proceedings. IEEE International Conference on Bioinformatics and Biomedicine · 2022Article
- Identifying Datasets for Cross-Study Analysis in dbGaP using PhenX.Scientific data · 2022Article
- SemClinBr - a multi-institutional and multi-specialty semantically annotated corpus for Portuguese clinical NLP tasks.Journal of biomedical semantics · 2022Article
- MedTAG: a portable and customizable annotation tool for biomedical documents.BMC medical informatics and decision making · 2021Article
- Data Normalization Improves Semantic Annotation - a Case Study of Rare Disease Name Annotation.Proceedings. IEEE International Conference on Bioinformatics and Biomedicine · 2021Article
- Improving broad-coverage medical entity linking with semantic type prediction and large-scale datasets.Journal of biomedical informatics · 2021Article
- Leveraging network analysis to evaluate biomedical named entity recognition tools.Scientific reports · 2021Article
- Ambiguity in medical concept normalization: An analysis of types and coverage in electronic health record datasets.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Automated Coding of Under-Studied Medical Concept Domains: Linking Physical Activity Reports to the International Classification of Functioning, Disability, and Health.Frontiers in digital health · 2021Article
- Data Integration Challenges for Machine Learning in Precision Medicine.Frontiers in medicine · 2021Review
- ECO-CollecTF: A Corpus of Annotated Evidence-Based Assertions in Biomedical Manuscripts.Frontiers in research metrics and analytics · 2021Article
- Community Approaches for Integrating Environmental Exposures into Human Models of Disease.Environmental health perspectives · 2020Article
- Enabling a fast annotation process with the Table2Annotation tool.Genomics & informatics · 2020Article
- Applying citizen science to gene, drug and disease relationship extraction from biomedical abstracts.Bioinformatics (Oxford, England) · 2020Article
- Named Entity Recognition and Relation Detection for Biomedical Information Extraction.Frontiers in cell and developmental biology · 2020Review
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The abundance and unstructured nature of biomedical texts, be it clinical or research content, impose significant challenges for the effective and efficient use of information and knowledge stored in such texts. Annotation of biomedical documents with machine intelligible semantics facilitates advanced, semantics-based text management, curation, indexing, and search. This paper focuses on annotation of biomedical entity mentions with concepts from relevant biomedical knowledge bases such as UMLS. As a result, the meaning of those mentions is unambiguously and explicitly defined, and thus made readily available for automated processing. This process is widely known as semantic annotation, and the tools that perform it are known as semantic annotators.Over the last dozen years, the biomedical research community has invested significant efforts in the development of biomedical semantic annotation technology. Aiming to establish grounds for further developments in this area, we review a selected set of state of the art biomedical semantic annotators, focusing particularly on general purpose annotators, that is, semantic annotation tools that can be customized to work with texts from any area of biomedicine. We also examine potential directions for further improvements of today's annotators which could make them even more capable of meeting the needs of real-world applications. To motivate and encourage further developments in this area, along the suggested and/or related directions, we review existing and potential practical applications and benefits of semantic annotators.
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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.