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Development of an online, publicly accessible naive Bayesian decision support tool for mammographic mass lesions based on the American College of Radiology (ACR) BI-RADS lexicon

PURPOSE: To develop and validate a decision support tool for mammographic mass lesions based on a standardized descriptor terminology (BI-RADS lexicon) to reduce variability of practice. MATERIALS AND METHODS: We used separate training data (1276 lesions, 138 malignant) and validation data (1177 les...

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書誌詳細
出版年:Eur Radiol
主要な著者: Benndorf, Matthias, Kotter, Elmar, Langer, Mathias, Herda, Christoph, Wu, Yirong, Burnside, Elizabeth S.
フォーマット: Artigo
言語:Inglês
出版事項: 2015
主題:
オンライン・アクセス:https://ncbi.nlm.nih.gov/pmc/articles/PMC4420692/
https://ncbi.nlm.nih.gov/pubmed/25576230
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s00330-014-3570-6
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