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X Demographics
Mendeley readers
| Title |
Predictive digital twin for optimizing patient-specific radiotherapy regimens under uncertainty in high-grade gliomas
|
|---|---|
| Published in |
Frontiers in Artificial Intelligence, October 2023
|
| DOI | 10.3389/frai.2023.1222612 |
| Pubmed ID | |
| Authors |
Anirban Chaudhuri, Graham Pash, David A. Hormuth, Guillermo Lorenzo, Michael Kapteyn, Chengyue Wu, Ernesto A. B. F. Lima, Thomas E. Yankeelov, Karen Willcox |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 1 | 17% |
| United States | 1 | 17% |
| Switzerland | 1 | 17% |
| Unknown | 3 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 50% |
| Members of the public | 3 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 17 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 3 | 18% |
| Student > Bachelor | 2 | 12% |
| Professor | 1 | 6% |
| Unspecified | 1 | 6% |
| Student > Master | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 9 | 53% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 3 | 18% |
| Medicine and Dentistry | 3 | 18% |
| Unspecified | 1 | 6% |
| Computer Science | 1 | 6% |
| Unknown | 9 | 53% |