Assessment of Machine Learning of Breast Pathology Structures for Automated Differentiation of Breast Cancer and High-Risk Proliferative Lesions

IMPORTANCE: Following recent US Food and Drug Administration approval, adoption of whole slide imaging in clinical settings may be imminent, and diagnostic accuracy, particularly among challenging breast biopsy specimens, may benefit from computerized diagnostic support tools. OBJECTIVE: To develop...

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Detalles Bibliográficos
Autores principales: Mercan, Ezgi, Mehta, Sachin, Bartlett, Jamen, Shapiro, Linda G., Weaver, Donald L., Elmore, Joann G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Association 2019
Materias:
Original Investigation
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6692690/
https://www.ncbi.nlm.nih.gov/pubmed/31397859
http://dx.doi.org/10.1001/jamanetworkopen.2019.8777

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6692690/
https://www.ncbi.nlm.nih.gov/pubmed/31397859
http://dx.doi.org/10.1001/jamanetworkopen.2019.8777

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