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Mendeley readers
Chapter title |
Mining Unexpected Associations for Signalling Potential Adverse Drug Reactions from Administrative Health Databases
|
---|---|
Chapter number | 101 |
Book title |
Advances in Knowledge Discovery and Data Mining
|
Published by |
Springer, Berlin, Heidelberg, April 2006
|
DOI | 10.1007/11731139_101 |
Book ISBNs |
978-3-54-033206-0, 978-3-54-033207-7
|
Authors |
Huidong Jin, Jie Chen, Chris Kelman, Hongxing He, Damien McAullay, Christine M. O’Keefe, Jin, Huidong, Chen, Jie, Kelman, Chris, He, Hongxing, McAullay, Damien, O’Keefe, Christine M. |
Mendeley readers
The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Korea, Republic of | 1 | 5% |
Taiwan | 1 | 5% |
Unknown | 17 | 89% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 9 | 47% |
Student > Doctoral Student | 2 | 11% |
Researcher | 2 | 11% |
Librarian | 1 | 5% |
Student > Bachelor | 1 | 5% |
Other | 3 | 16% |
Unknown | 1 | 5% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 8 | 42% |
Pharmacology, Toxicology and Pharmaceutical Science | 3 | 16% |
Mathematics | 2 | 11% |
Medicine and Dentistry | 2 | 11% |
Nursing and Health Professions | 1 | 5% |
Other | 1 | 5% |
Unknown | 2 | 11% |