Artificial intelligence system reduces false-positive findings in the interpretation of breast ultrasound exams

Though consistently shown to detect mammographically occult cancers, breast ultrasound has been noted to have high false-positive rates. In this work, we present an AI system that achieves radiologist-level accuracy in identifying breast cancer in ultrasound images. Developed on 288,767 exams, consi...

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Detalles Bibliográficos
Autores principales: Shen, Yiqiu, Shamout, Farah E., Oliver, Jamie R., Witowski, Jan, Kannan, Kawshik, Park, Jungkyu, Wu, Nan, Huddleston, Connor, Wolfson, Stacey, Millet, Alexandra, Ehrenpreis, Robin, Awal, Divya, Tyma, Cathy, Samreen, Naziya, Gao, Yiming, Chhor, Chloe, Gandhi, Stacey, Lee, Cindy, Kumari-Subaiya, Sheila, Leonard, Cindy, Mohammed, Reyhan, Moczulski, Christopher, Altabet, Jaime, Babb, James, Lewin, Alana, Reig, Beatriu, Moy, Linda, Heacock, Laura, Geras, Krzysztof J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8463596/
https://www.ncbi.nlm.nih.gov/pubmed/34561440
http://dx.doi.org/10.1038/s41467-021-26023-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8463596/
https://www.ncbi.nlm.nih.gov/pubmed/34561440
http://dx.doi.org/10.1038/s41467-021-26023-2

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