BI-RADS categorization as a predictor of malignancy.

By S. Orel, Nicole Kay, C. Reynolds, D. Sullivan. 1999

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

A case-based interpretable deep learning model for classification of mass lesions in digital mammography (2021, background): “In mammography, the initial clinical decision is expressed as a BI-RADS category of 1 to 5, corresponding to the recommendation of whether the patient needs a biopsy [36, 46].”
INbreast: toward a full-field digital mammographic database. (2012, background): “In case of categories 4 and 5, a biopsy is needed to exclude or confirm malignancy (10).”
Imaging Intratumor Heterogeneity: Role in Therapy Response, Resistance, and Clinical Outcome (2014, methodology): “Indeed, spiculate morphology is part of the BI-RADS (Breast Imaging Reporting andData System) lexicon that classifies breast lesions as "radiologically malignant" (22).”
Computer-Aided Detection and Diagnosis in Mammography (2005, background): “RADSTM final assessment rating is an indicator of the likelihood of malignancy [5].”
Breast imaging reporting and data system (BI-RADS). (2002, background): “PPV Liberman [5] 0/8 (0) 120/355 (34) 105/129 (81) Orel [6] 3/141 (2) 279/936 (30) 165/170 (97) Lacquement [4] 9/322 (3) 54/234 (23) 97/106 (92)”