Cancer Risk Prediction Paradigm Shift: Using Artificial Intelligence to Improve Performance and Health Equity

Christoph I Lee^{1

2

3}, Joann G Elmore⁴

Affiliations

¹ Department of Radiology, University of Washington School of Medicine, Seattle, WA, USA.
² De partment of Health Systems and Population Health, University of Washington School of Public Health, Seattle, WA, USA.
³ Hutchinson Institute for Cancer Outcomes Research, Fred Hutchinson Cancer Center, Seattle, WA, USA.
⁴ Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.

Editorial

Christoph I Lee et al. J Natl Cancer Inst. 2022.

. 2022 Oct 6;114(10):1317-1319.

doi: 10.1093/jnci/djac143.

Christoph I Lee^{1

2

3}, Joann G Elmore⁴

¹ Department of Radiology, University of Washington School of Medicine, Seattle, WA, USA.
² De partment of Health Systems and Population Health, University of Washington School of Public Health, Seattle, WA, USA.
³ Hutchinson Institute for Cancer Outcomes Research, Fred Hutchinson Cancer Center, Seattle, WA, USA.
⁴ Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.

No abstract available

Comment on

Deep Learning vs Traditional Breast Cancer Risk Models to Support Risk-Based Mammography Screening.
Lehman CD, Mercaldo S, Lamb LR, King TA, Ellisen LW, Specht M, Tamimi RM. Lehman CD, et al. J Natl Cancer Inst. 2022 Oct 6;114(10):1355-1363. doi: 10.1093/jnci/djac142. J Natl Cancer Inst. 2022. PMID: 35876790 Free PMC article.

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