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Mendeley readers
Chapter title |
Mining Healthcare Data with Temporal Association Rules: Improvements and Assessment for a Practical Use
|
---|---|
Chapter number | 3 |
Book title |
Artificial Intelligence in Medicine
|
Published by |
Springer, Berlin, Heidelberg, July 2009
|
DOI | 10.1007/978-3-642-02976-9_3 |
Book ISBNs |
978-3-64-202975-2, 978-3-64-202976-9
|
Authors |
Stefano Concaro, Lucia Sacchi, Carlo Cerra, Pietro Fratino, Riccardo Bellazzi, Concaro, Stefano, Sacchi, Lucia, Cerra, Carlo, Fratino, Pietro, Bellazzi, Riccardo |
Mendeley readers
The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 1 | 3% |
Spain | 1 | 3% |
United States | 1 | 3% |
Canada | 1 | 3% |
Unknown | 31 | 89% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 13 | 37% |
Researcher | 9 | 26% |
Student > Master | 4 | 11% |
Student > Postgraduate | 3 | 9% |
Professor > Associate Professor | 3 | 9% |
Other | 2 | 6% |
Unknown | 1 | 3% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 21 | 60% |
Engineering | 3 | 9% |
Medicine and Dentistry | 2 | 6% |
Mathematics | 1 | 3% |
Business, Management and Accounting | 1 | 3% |
Other | 4 | 11% |
Unknown | 3 | 9% |