Breast Imaging in the Era of Big Data: Structured Reporting and Data Mining
Laurie R. Margolies, Gaurav Shankar Pandey, Eliot R. Horowitz, David S. Mendelson · American Journal of Roentgenology · 2015
OBJECTIVE: The purpose of this article is to describe structured reporting and the development of large databases for use in data mining in breast imaging. CONCLUSION: The results of millions of breast imaging examinations are reported with structured tools based on the BI-RADS lexicon. Much of these data are stored in accessible media. Robust computing power creates great opportunity for data scientists and breast imagers to collaborate to improve breast cancer detection and optimize screening algorithms. Data mining can create knowledge, but the questions asked and their complexity require extremely powerful and agile databases. New data technologies can facilitate outcomes research and precision medicine.