ArticleJournal of biomedical informatics2013
Leveraging concept-based approaches to identify potential phyto-therapies.
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 4 papers.
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.
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
4 citing papers in PubMed.
- Identifying Supplement Use Within Clinical Notes: An Applicationof Natural Language Processing.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2018Article
- Identifying Plant-Human Disease Associations in Biomedical Literature: A Case Study.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2016Article
- Applying MetaMap to Medline for identifying novel associations in a large clinical dataset: a feasibility analysis.Journal of the American Medical Informatics Association : JAMIAArticle
- Systems biology approaches for identifying adverse drug reactions and elucidating their underlying biological mechanisms.Wiley interdisciplinary reviews. Systems biology and medicineReview
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
The potential of plant-based remedies has been documented in both traditional and contemporary biomedical literature. Such types of text sources may thus be sources from which one might identify potential plant-based therapies ("phyto-therapies"). Concept-based analytic approaches have been shown to uncover knowledge embedded within biomedical literature. However, to date there has been limited attention towards leveraging such techniques for the identification of potential phyto-therapies. This study presents concept-based analytic approaches for the retrieval and ranking of associations between plants and human diseases. Focusing on identification of phyto-therapies described in MEDLINE, both MeSH descriptors used for indexing and MetaMap inferred UMLS concepts are considered. Furthermore, the identification and ranking consider both direct (i.e., plant concepts directly correlated with disease concepts) and inferred (i.e., plant concepts associated with disease concepts based on shared signs and symptoms) relationships. Based on the two scoring methodologies used in this study, it was found that a Vector Space Model approach outperformed probabilistic reliability based inferences. An evaluation of the approach is provided based on therapeutic interventions catalogued in both ClinicalTrials.gov and NDF-RT. The promising findings from this feasibility study highlight the challenges and applicability of concept-based analytic strategies for distilling phyto-therapeutic knowledge from text based knowledge sources like MEDLINE.
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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.