首页|Modeling false positive error making patterns in radiology trainees for improved mammography education

Modeling false positive error making patterns in radiology trainees for improved mammography education

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  • NSTL
  • Elsevier
Introduction: While mammography notably contributes to earlier detection of breast cancer, it has its limitations, including a large number of false positive exams. Improved radiology education could potentially contribute to alleviating this issue. Toward this goal, in this paper we propose an algorithm for modeling of false positive error making among radiology trainees. Identifying troublesome locations for the trainees could focus their training and in turn improve their performance.

Breast cancerRadiology educationComputer visionMachine learning

Mazurowski, Maciej A.、Zhang, Jing、Silber, James I.

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Duke Univ, Sch Med, Dept Radiol, Durham, NC USA

Duke Univ, Dept Biomed Engn, Pratt Sch Engn, Durham, NC 27706 USA

2015

10.1016/j.jbi.2015.01.007

Journal of biomedical informatics.

Journal of biomedical informatics.

ISSN：1532-0464
年,卷(期)：2015.54
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