Breast lesion shape and margin evaluation: BI-RADS based metrics understate radiologists' actual levels of agreement

By M. Rawashdeh, S. Lewis, M. Zaitoun, P. Brennan. 2018

17 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Pathology and Forensic Medicine, Radiology, Nuclear Medicine and Imaging

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

1. Cynthia Rudin
2. Alina Jade Barnett
3. Chaofan Tao
4. Tong Wang
5. Octavio Loyola-González
6. Berk Ustun
7. Lesia Semenova
8. Peter Hase

In Radiology, Nuclear Medicine and Imaging

1. Cynthia Rudin

Citations in the corpus

• A case-based interpretable deep learning model for classification of mass lesions in digital mammography (2021, positive): “We use Cohen κ to compare our model’s agreement to the agreement of physicians with each other from previous studies [37, 1, 5, 39, 31].”