Mining FDA drug labels using an unsupervised learning technique--topic modeling
about
An overview of topic modeling and its current applications in bioinformaticsMultinomial modeling and an evaluation of common data-mining algorithms for identifying signals of disproportionate reporting in pharmacovigilance databases.A phenome-guided drug repositioning through a latent variable model.Proceedings of the 2011 MidSouth Computational Biology and Bioinformatics Society (MCBIOS) conference. Introduction.Proceedings of the 2012 MidSouth Computational Biology and Bioinformatics Society (MCBIOS) conference. Introduction.Investigating drug repositioning opportunities in FDA drug labels through topic modelingOf text and gene--using text mining methods to uncover hidden knowledge in toxicogenomicsRedundancy in electronic health record corpora: analysis, impact on text mining performance and mitigation strategiesMining FDA drug labels for medical conditionsMining hidden knowledge for drug safety assessment: topic modeling of LiverTox as a case study.A systems approach for analysis of high content screening assay data with topic modelingRedundancy-aware topic modeling for patient record notes.Semantic processing to identify adverse drug event information from black box warningsDiscovering associations among diagnosis groups using topic modeling.Case-based reasoning using electronic health records efficiently identifies eligible patients for clinical trials.Text mining for identifying topics in the literatures about adolescent substance use and depressionLeveraging graph topology and semantic context for pharmacovigilance through twitter-streams.Predicting the Drug Safety for Traditional Chinese Medicine through a Comparative Analysis of Withdrawn Drugs Using Pharmacological Network.Deep Patient: An Unsupervised Representation to Predict the Future of Patients from the Electronic Health Records.Toward predictive models for drug-induced liver injury in humans: are we there yet?Integrative approaches for predicting in vivo effects of chemicals from their structural descriptors and the results of short-term biological assays.From Big Data to Smart Data for Pharmacovigilance: The Role of Healthcare Databases and Other Emerging Sources.Facilitating prediction of adverse drug reactions by using knowledge graphs and multi-label learning models.Mining Adverse Events of Dietary Supplements from Product Labels by Topic Modeling.Systematic identification of latent disease-gene associations from PubMed articles.Topic Modeling of Smoking- and Cessation-Related Posts to the American Cancer Society's Cancer Survivor Network (CSN): Implications for Cessation Treatment for Cancer Survivors Who Smoke.Semantic processing to identify adverse drug event information from black box warnings.
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P2860
Mining FDA drug labels using an unsupervised learning technique--topic modeling
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2011 nî lūn-bûn
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2011 թուականի Հոկտեմբերին հրատարակուած գիտական յօդուած
@hyw
2011 թվականի հոտեմբերին հրատարակված գիտական հոդված
@hy
2011年の論文
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2011年論文
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2011年論文
@zh-hant
2011年論文
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2011年論文
@zh-mo
2011年論文
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2011年论文
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name
Mining FDA drug labels using an unsupervised learning technique--topic modeling
@ast
Mining FDA drug labels using an unsupervised learning technique--topic modeling
@en
Mining FDA drug labels using an unsupervised learning technique--topic modeling
@nl
type
label
Mining FDA drug labels using an unsupervised learning technique--topic modeling
@ast
Mining FDA drug labels using an unsupervised learning technique--topic modeling
@en
Mining FDA drug labels using an unsupervised learning technique--topic modeling
@nl
prefLabel
Mining FDA drug labels using an unsupervised learning technique--topic modeling
@ast
Mining FDA drug labels using an unsupervised learning technique--topic modeling
@en
Mining FDA drug labels using an unsupervised learning technique--topic modeling
@nl
P2093
P2860
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P1476
Mining FDA drug labels using an unsupervised learning technique--topic modeling
@en
P2093
Halil Bisgin
Xiaowei Xu
Zhichao Liu
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P2888
P356
10.1186/1471-2105-12-S10-S11
P478
12 Suppl 10
P50
P577
2011-10-18T00:00:00Z
P6179
1017224302