The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Mendeley readers
| Title |
Head and neck cancer treatment outcome prediction: a comparison between machine learning with conventional radiomics features and deep learning radiomics
|
|---|---|
| Published in |
Frontiers in Medicine, August 2023
|
| DOI | 10.3389/fmed.2023.1217037 |
| Pubmed ID | |
| Authors |
Bao Ngoc Huynh, Aurora Rosvoll Groendahl, Oliver Tomic, Kristian Hovde Liland, Ingerid Skjei Knudtsen, Frank Hoebers, Wouter van Elmpt, Eirik Malinen, Einar Dale, Cecilia Marie Futsaether |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 18 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 2 | 11% |
| Student > Bachelor | 1 | 6% |
| Other | 1 | 6% |
| Student > Master | 1 | 6% |
| Researcher | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 12 | 67% |
| Readers by discipline | Count | As % |
|---|---|---|
| Physics and Astronomy | 2 | 11% |
| Computer Science | 1 | 6% |
| Arts and Humanities | 1 | 6% |
| Medicine and Dentistry | 1 | 6% |
| Engineering | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 12 | 67% |