| scholarly article | Q13442814 |
| P8978 | DBLP publication ID | journals/bmcbi/BisginLFXT11 |
| P6179 | Dimensions Publication ID | 1017224302 |
| P356 | DOI | 10.1186/1471-2105-12-S10-S11 |
| P932 | PMC publication ID | 3236833 |
| P698 | PubMed publication ID | 22166012 |
| P50 | author | Weida Tong | Q96475222 |
| P2093 | author name string | Hong Fang | |
| Zhichao Liu | |||
| Xiaowei Xu | |||
| Halil Bisgin | |||
| P2860 | cites work | Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders | Q24558589 |
| Timing of new black box warnings and withdrawals for prescription medications | Q28216033 | ||
| Finding complex biological relationships in recent PubMed articles using Bio-LDA | Q28477467 | ||
| Extraction of semantic biomedical relations from text using conditional random fields | Q28754563 | ||
| Identifying biological concepts from a protein-related corpus with a probabilistic topic model | Q33233422 | ||
| Using the literature-based discovery paradigm to investigate drug mechanisms | Q33359167 | ||
| Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders. | Q34010718 | ||
| What is prescription labeling communicating to doctors about hepatotoxic drugs? A study of FDA approved product labeling | Q35837119 | ||
| "Black box" 101: How the Food and Drug Administration evaluates, communicates, and manages drug benefit/risk | Q36357738 | ||
| Inside the black box: current policies and concerns with the United States Food and Drug Administration's highest drug safety warning system | Q37743401 | ||
| Mapping adverse drug reactions in chemical space. | Q39881783 | ||
| Fish oil, Raynaud's syndrome, and undiscovered public knowledge | Q69703977 | ||
| How adverse drug reactions can play a role in innovative drug research | Q70992416 | ||
| P921 | main subject | unsupervised learning | Q1152135 |
| topic model | Q3532085 | ||
| Topic modeling | Q96468792 | ||
| P304 | page(s) | S11 | |
| P577 | publication date | 2011-10-18 | |
| P1433 | published in | BMC Bioinformatics | Q4835939 |
| P1476 | title | Mining FDA drug labels using an unsupervised learning technique--topic modeling | |
| P478 | volume | 12 Suppl 10 |
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| Q36853573 | Predicting the Drug Safety for Traditional Chinese Medicine through a Comparative Analysis of Withdrawn Drugs Using Pharmacological Network |
| Q34099736 | Proceedings of the 2011 MidSouth Computational Biology and Bioinformatics Society (MCBIOS) conference. Introduction |
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| Q35097852 | Semantic processing to identify adverse drug event information from black box warnings |
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| Q51429997 | 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. |
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