ArticleJournal of biomedical informatics2013
Unsupervised mining of frequent tags for clinical eligibility text indexing.
Article in Journal of biomedical informatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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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.
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.
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Who cites it
18 citing papers in PubMed.
- A review of research on eligibility criteria for clinical trials.Clinical and experimental medicine · 2023Review
- ELaPro, a LOINC-mapped core dataset for top laboratory procedures of eligibility screening for clinical trials.BMC medical research methodology · 2022Article
- Core Data Elements in Acute Myeloid Leukemia: A Unified Medical Language System-Based Semantic Analysis and Experts' Review.JMIR medical informatics · 2019Article
- Bridging semantics and syntax with graph algorithms-state-of-the-art of extracting biomedical relations.Briefings in bioinformatics · 2017Article
- Comparing and Contrasting A Priori and A Posteriori Generalizability Assessment of Clinical Trials on Type 2 Diabetes Mellitus.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2017Article
- Prediction of black box warning by mining patterns of Convergent Focus Shift in clinical trial study populations using linked public data.Journal of biomedical informatics · 2016Article
- IDENTIFICATION OF QUESTIONABLE EXCLUSION CRITERIA IN MENTAL DISORDER CLINICAL TRIALS USING A MEDICAL ENCYCLOPEDIA.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2016Article
- How Have Cancer Clinical Trial Eligibility Criteria Evolved Over Time?AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2016Article
- Combining expert knowledge and knowledge automatically acquired from electronic data sources for continued ontology evaluation and improvement.Journal of biomedical informatics · 2015Article
- Clinical Research Informatics: Recent Advances and Future Directions.Yearbook of medical informatics · 2015Article
- Visual aggregate analysis of eligibility features of clinical trials.Journal of biomedical informatics · 2015Article
- Case-based reasoning using electronic health records efficiently identifies eligible patients for clinical trials.Journal of the American Medical Informatics Association : JAMIA · 2015Article
- Adaptive semantic tag mining from heterogeneous clinical research texts.Methods of information in medicine · 2015Article
- Trend and Network Analysis of Common Eligibility Features for Cancer Trials in ClinicalTrials.gov.Smart health : international conference, ICSH ... ICSH (Conference : Smart Health) · 2014Article
- A method for analyzing commonalities in clinical trial target populations.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2014Article
- A distribution-based method for assessing the differences between clinical trial target populations and patient populations in electronic health records.Applied clinical informatics · 2014Article
- ClinicalTrials.gov as a data source for semi-automated point-of-care trial eligibility screening.PloS one · 2014Article
- eTACTS: a method for dynamically filtering clinical trial search results.Journal of biomedical informatics · 2013Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Clinical text, such as clinical trial eligibility criteria, is largely underused in state-of-the-art medical search engines due to difficulties of accurate parsing. This paper proposes a novel methodology to derive a semantic index for clinical eligibility documents based on a controlled vocabulary of frequent tags, which are automatically mined from the text. We applied this method to eligibility criteria on ClinicalTrials.gov and report that frequent tags (1) define an effective and efficient index of clinical trials and (2) are unlikely to grow radically when the repository increases. We proposed to apply the semantic index to filter clinical trial search results and we concluded that frequent tags reduce the result space more efficiently than an uncontrolled set of UMLS concepts. Overall, unsupervised mining of frequent tags from clinical text leads to an effective semantic index for the clinical eligibility documents and promotes their computational reuse.
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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.