Deep Neural Networks Improve Radiologists’ Performance in Breast Cancer Screening

We present a deep convolutional neural network for breast cancer screening exam classification, trained, and evaluated on over 200 000 exams (over 1 000 000 images). Our network achieves an AUC of 0.895 in predicting the presence of cancer in the breast, when tested on the screening population. We a...

Descripción completa

Guardado en:
Detalles Bibliográficos
Publicado en:IEEE Trans Med Imaging
Autores principales: Wu, Nan, Phang, Jason, Park, Jungkyu, Shen, Yiqiu, Huang, Zhe, Zorin, Masha, Jastrzębski, Stanisław, Févry, Thibault, Katsnelson, Joe, Kim, Eric, Wolfson, Stacey, Parikh, Ujas, Gaddam, Sushma, Lin, Leng Leng Young, Ho, Kara, Weinstein, Joshua D., Reig, Beatriu, Gao, Yiming, Toth, Hildegard, Pysarenko, Kristine, Lewin, Alana, Lee, Jiyon, Airola, Krystal, Mema, Eralda, Chung, Stephanie, Hwang, Esther, Samreen, Naziya, Kim, S. Gene, Heacock, Laura, Moy, Linda, Cho, Kyunghyun, Geras, Krzysztof J.
Formato: Artigo
Lenguaje:Inglês
Publicado: 2019
Materias:
Article
Acceso en línea:https://ncbi.nlm.nih.gov/pmc/articles/PMC7427471/
https://ncbi.nlm.nih.gov/pubmed/31603772
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/TMI.2019.2945514
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares