Will Machine Learning Tip the Balance in Breast Cancer Screening?

JAMA Oncol. 2017 Nov 1;3(11):1463-1464. doi: 10.1001/jamaoncol.2017.0473.

Authors

Andrew D Trister^{1

2}, Diana S M Buist³, Christoph I Lee⁴

Affiliations

¹ Department of Radiation Medicine, Oregon Health and Science University, Portland.
² Sage Bionetworks, Seattle, Washington.
³ Kaiser Permanente Washington Health Research Institute, Seattle, Washington.
⁴ Hutchinson Institute for Cancer Outcomes Research, Fred Hutchinson Cancer Research Center, Department of Radiology, University of Washington School of Medicine, Seattle.

No abstract available

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Breast Neoplasms / diagnostic imaging*
Breast Neoplasms / psychology
Databases, Factual
Early Detection of Cancer / methods*
Female
Humans
Image Interpretation, Computer-Assisted / methods*
Mammography
Sensitivity and Specificity
Unsupervised Machine Learning

Grants and funding

P01 CA154292/CA/NCI NIH HHS/United States