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Mendeley readers
Chapter title |
Automated Detection of New or Evolving Melanocytic Lesions Using a 3D Body Model
|
---|---|
Chapter number | 74 |
Book title |
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014
|
Published in |
Lecture notes in computer science, September 2014
|
DOI | 10.1007/978-3-319-10404-1_74 |
Pubmed ID | |
Book ISBNs |
978-3-31-910403-4, 978-3-31-910404-1
|
Authors |
Federica Bogo, Javier Romero, Enoch Peserico, Michael J. Black |
Editors |
Polina Golland, Nobuhiko Hata, Christian Barillot, Joachim Hornegger, Robert Howe |
Mendeley readers
The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 1 | 3% |
United States | 1 | 3% |
Unknown | 37 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 14 | 36% |
Other | 7 | 18% |
Researcher | 6 | 15% |
Student > Master | 3 | 8% |
Professor | 1 | 3% |
Other | 3 | 8% |
Unknown | 5 | 13% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 10 | 26% |
Engineering | 7 | 18% |
Medicine and Dentistry | 6 | 15% |
Mathematics | 2 | 5% |
Biochemistry, Genetics and Molecular Biology | 2 | 5% |
Other | 3 | 8% |
Unknown | 9 | 23% |