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...

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Detalles Bibliográficos
Autores principales: Hinton, Benjamin, Ma, Lin, Mahmoudzadeh, Amir Pasha, Malkov, Serghei, Fan, Bo, Greenwood, Heather, Joe, Bonnie, Lee, Vivian, Kerlikowske, Karla, Shepherd, John
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Research Article
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

Internet

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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