Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6855586 | Expert Systems with Applications | 2016 | 10 Pages |
Abstract
Our user model can be used to select the most challenging cases for each trainee from the perspective of committing false positive errors. Our model improved the status quo of case presentation with random selection to trainee in breast tomosynthesis.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Wang Mengyu, Wang Meng, Lars J. Grimm, Maciej A. Mazurowski,