ReviewJournal of biomedical informatics2009
Empirical distributional semantics: methods and biomedical applications.
Review in Journal of biomedical informatics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 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
59 citing papers in PubMed.
- Perplexity and proximity: Large language model perplexity complements semantic distance metrics for the detection of incoherent speech.Journal of biomedical informatics · 2025Article
- ARCH: Large-scale knowledge graph via aggregated narrative codified health records analysis.Journal of biomedical informatics · 2025Article
- Hyperdimensional computing: A fast, robust, and interpretable paradigm for biological data.PLoS computational biology · 2024Review
- Article
- Fully automated detection of formal thought disorder with Time-series Augmented Representations for Detection of Incoherent Speech (TARDIS).Journal of biomedical informatics · 2022Article
- Behavioral Activation and Depression Symptomatology: Longitudinal Assessment of Linguistic Indicators in Text-Based Therapy Sessions.Journal of medical Internet research · 2021Article
- Augmenting aer2vec: Enriching distributed representations of adverse event report data with orthographic and lexical information.Journal of biomedical informatics · 2021Article
- Perceived Utility and Characterization of Personal Google Search Histories to Detect Data Patterns Proximal to a Suicide Attempt in Individuals Who Previously Attempted Suicide: Pilot Cohort Study.Journal of medical Internet research · 2021Article
- Better synonyms for enriching biomedical search.Journal of the American Medical Informatics Association : JAMIA · 2020Article
- Diabetes Self-Management in the Age of Social Media: Large-Scale Analysis of Peer Interactions Using Semiautomated Methods.JMIR medical informatics · 2020Article
- Health information needs regarding diabetes mellitus in China: an internet-based analysis.BMC public health · 2020Article
- Exploring Novel Computable Knowledge in Structured Drug Product Labels.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2020Article
- The Centroid Cannot Hold: Comparing Sequential and Global Estimates of Coherence as Indicators of Formal Thought Disorder.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2020Article
- Exploring semantic deep learning for building reliable and reusable one health knowledge from PubMed systematic reviews and veterinary clinical notes.Journal of biomedical semantics · 2019Article
- Using word embeddings to expand terminology of dietary supplements on clinical notes.JAMIA open · 2019Article
- Feature extraction for phenotyping from semantic and knowledge resources.Journal of biomedical informatics · 2019Article
- Rapamycin - mTOR + BRAF = ? Using relational similarity to find therapeutically relevant drug-gene relationships in unstructured text.Journal of biomedical informatics · 2019Article
- Article
- A global network of biomedical relationships derived from text.Bioinformatics (Oxford, England) · 2018Article
- Expanding a radiology lexicon using contextual patterns in radiology reports.Journal of the American Medical Informatics Association : JAMIA · 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
2 authors.
Funding
Abstract
Over the past 15 years, a range of methods have been developed that are able to learn human-like estimates of the semantic relatedness between terms from the way in which these terms are distributed in a corpus of unannotated natural language text. These methods have also been evaluated in a number of applications in the cognitive science, computational linguistics and the information retrieval literatures. In this paper, we review the available methodologies for derivation of semantic relatedness from free text, as well as their evaluation in a variety of biomedical and other applications. Recent methodological developments, and their applicability to several existing applications are also discussed.
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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.