ArticlePacific Symposium on Biocomputing. Pacific Symposium on Biocomputing2018
Identifying natural health product and dietary supplement information within adverse event reporting systems.
Article in Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed.
- Broadening the capture of natural products mentioned in FAERS using fuzzy string-matching and a Siamese neural network.Scientific reports · 2024Article
- Developing a Knowledge Graph for Pharmacokinetic Natural Product-Drug Interactions.Journal of biomedical informatics · 2023Article
- iDISK: the integrated DIetary Supplements Knowledge base.Journal of the American Medical Informatics Association : JAMIA · 2020Article
- Identifying Herbal Adverse Events From Spontaneous Reporting Systems Using Taxonomic Name Resolution Approach.Bioinformatics and biology insights · 2020Article
- Normalizing Dietary Supplement Product Names Using the RxNorm Model.Studies in health technology and informatics · 2019Article
- Detecting Signals of Dietary Supplement Adverse Events from the CFSAN Adverse Event Reporting System (CAERS).AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2019Article
- 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
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
Data on safety and efficacy issues associated with natural health products and dietary supplements (NHP&S) remains largely cloistered within domain specific databases or embedded within general biomedical data sources. A major challenge in leveraging analytic approaches on such data is due to the inefficient ability to retrieve relevant data, which includes a general lack of interoperability among related sources. This study developed a thesaurus of NHP&S ingredient terms that can be used by existing biomedical natural language processing (NLP) tools for extracting information of interest. This process was evaluated relative to intervention name strings sampled from the United States Food and Drug Administration Adverse Event Reporting System (FAERS). A use case was used to demonstrate the potential to utilize FAERS for monitoring NHP&S adverse events. The results from this study provide insights on approaches for identifying additional knowledge from extant repositories of knowledge, and potentially as information that can be included into larger curation efforts.
Indexed as
Identifiers
29218888PMC5725198What OpenQuestion holds
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.