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Deep learning networks find unique mammographic differences in previous negative mammograms between interval and screen-detected cancers: a case-case study
BACKGROUND: To determine if mammographic features from deep learning networks can be applied in breast cancer to identify groups at interval invasive cancer risk due to masking beyond using traditional breast density measures. METHODS: Full-field digital screening mammograms acquired in our clinics...
Autores principales: | Hinton, Benjamin, Ma, Lin, Mahmoudzadeh, Amir Pasha, Malkov, Serghei, Fan, Bo, Greenwood, Heather, Joe, Bonnie, Lee, Vivian, Kerlikowske, Karla, Shepherd, John |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6589178/ https://www.ncbi.nlm.nih.gov/pubmed/31228956 http://dx.doi.org/10.1186/s40644-019-0227-3 |
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