External validation of a publicly available computer assisted diagnostic tool for mammographic mass lesions with two high prevalence research datasets.
By M. Benndorf, E. Burnside, Christoph Herda, M. Langer, E. Kotter. 2015
6 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Oncology, Pulmonary and Respiratory Medicine
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Cynthia Rudin
- Alina Jade Barnett
- Chaofan Tao
- Tong Wang
- Octavio Loyola-González
- Berk Ustun
- Lesia Semenova
- Peter Hase
In Oncology
In Pulmonary and Respiratory Medicine
Citations in the corpus
- A case-based interpretable deep learning model for classification of mass lesions in digital mammography (2021, background): “Some studies have reported better performance in predicting malignancy from BI-RADS features [19, 6, 7].”