| Title |
Text Mining for Adverse Drug Events: the Promise, Challenges, and State of the Art
|
|---|---|
| Published in |
Drug Safety, August 2014
|
| DOI | 10.1007/s40264-014-0218-z |
| Pubmed ID | |
| Authors |
Rave Harpaz, Alison Callahan, Suzanne Tamang, Yen Low, David Odgers, Sam Finlayson, Kenneth Jung, Paea LePendu, Nigam H. Shah |
| Abstract |
Text mining is the computational process of extracting meaningful information from large amounts of unstructured text. It is emerging as a tool to leverage underutilized data sources that can improve pharmacovigilance, including the objective of adverse drug event (ADE) detection and assessment. This article provides an overview of recent advances in pharmacovigilance driven by the application of text mining, and discusses several data sources-such as biomedical literature, clinical narratives, product labeling, social media, and Web search logs-that are amenable to text mining for pharmacovigilance. Given the state of the art, it appears text mining can be applied to extract useful ADE-related information from multiple textual sources. Nonetheless, further research is required to address remaining technical challenges associated with the text mining methodologies, and to conclusively determine the relative contribution of each textual source to improving pharmacovigilance. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 2 | 40% |
| Switzerland | 1 | 20% |
| Unknown | 2 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 276 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | <1% |
| Netherlands | 1 | <1% |
| Brazil | 1 | <1% |
| Canada | 1 | <1% |
| Finland | 1 | <1% |
| Japan | 1 | <1% |
| Slovenia | 1 | <1% |
| Unknown | 268 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 62 | 22% |
| Researcher | 40 | 14% |
| Student > Master | 40 | 14% |
| Student > Bachelor | 22 | 8% |
| Student > Postgraduate | 14 | 5% |
| Other | 53 | 19% |
| Unknown | 45 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 85 | 31% |
| Medicine and Dentistry | 39 | 14% |
| Pharmacology, Toxicology and Pharmaceutical Science | 15 | 5% |
| Engineering | 15 | 5% |
| Agricultural and Biological Sciences | 11 | 4% |
| Other | 51 | 18% |
| Unknown | 60 | 22% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 December 2022.
All research outputs
#6,316,877
of 25,257,066 outputs
Outputs from Drug Safety
#691
of 1,804 outputs
Outputs of similar age
#55,947
of 243,014 outputs
Outputs of similar age from Drug Safety
#12
of 22 outputs
Altmetric has tracked 25,257,066 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 1,804 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.1. This one has gotten more attention than average, scoring higher than 61% of its peers.
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We're also able to compare this research output to 22 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.