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JNCI Journal of the National Cancer Institute 2003 95(4):250-252; doi:10.1093/jnci/95.4.250
© 2003 by Oxford University Press
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Journal of the National Cancer Institute, Vol. 95, No. 4, 250-252, February 19, 2003
© 2003 Oxford University Press


EDITORIAL

Does Practice Make Perfect When Interpreting Mammography? Part II

Joann G. Elmore, Diana L. Miglioretti, Patricia A. Carney

Affiliations of authors: J. G. Elmore (Department of Internal Medicine), D. L. Miglioretti (Center for Health Studies, Group Health Cooperative and Department of Biostatistics), University of Washington, Seattle; P. A. Carney, Department of Community and Family Medicine, Dartmouth Medical School, Hanover, NH.

Correspondence to: Joann G. Elmore, M.D., M.P.H., Department of Internal Medicine, University of Washington School of Medicine, Harborview Medical Center, 325 Ninth Ave., Box 359780, Seattle, WA 98104-2499 (e-mail: jelmore@u.washington.edu).

The first 150 words of the full text of this article appear below.

"The art of the practice of medicine is to be learned only by experience; ‘tis not an inheritance; it cannot be revealed. Learn to see, learn to hear, learn to feel, learn to smell, and know that by practice alone can you become expert."

Sir William Osler (1)

The accuracy of screening mammography relies on a human interpreter. It seems intuitive that high levels of accuracy would occur for radiologists who routinely interpret high volumes, have many years of experience, and who audit the results of women undergoing breast biopsies at their recommendation. This statement, although based on common sense, is not supported by the analyses presented by Beam et al. (2) in this issue of the Journal.

Beam et al. studied the association between self-reported annual interpretation volume and radiologist accuracy in screening mammography. The authors asked 110 U.S. radiologists to interpret a test set . . . [Full Text of this Article]

WHAT DEFINES AN EXPERIENCED MAMMOGRAPHER?

DO ARTIFICIAL TEST ENVIRONMENTS REFLECT THE REAL WORLD?

COMPLEX STATISTICAL MODELS—SHOULD WE BELIEVE THEM?

WHAT SHOULD WOMEN DO?

WHAT SHOULD RADIOLOGISTS DO?


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