Nature Communications (Sep 2021)
Artificial intelligence system reduces false-positive findings in the interpretation of breast ultrasound exams
- Yiqiu Shen,
- Farah E. Shamout,
- Jamie R. Oliver,
- Jan Witowski,
- Kawshik Kannan,
- Jungkyu Park,
- Nan Wu,
- Connor Huddleston,
- Stacey Wolfson,
- Alexandra Millet,
- Robin Ehrenpreis,
- Divya Awal,
- Cathy Tyma,
- Naziya Samreen,
- Yiming Gao,
- Chloe Chhor,
- Stacey Gandhi,
- Cindy Lee,
- Sheila Kumari-Subaiya,
- Cindy Leonard,
- Reyhan Mohammed,
- Christopher Moczulski,
- Jaime Altabet,
- James Babb,
- Alana Lewin,
- Beatriu Reig,
- Linda Moy,
- Laura Heacock,
- Krzysztof J. Geras
Affiliations
- Yiqiu Shen
- Center for Data Science, New York University
- Farah E. Shamout
- Engineering Division, NYU Abu Dhabi
- Jamie R. Oliver
- Department of Radiology, NYU Grossman School of Medicine
- Jan Witowski
- Department of Radiology, NYU Grossman School of Medicine
- Kawshik Kannan
- Department of Computer Science, Courant Institute, New York University
- Jungkyu Park
- Vilcek Institute of Graduate Biomedical Sciences, NYU Grossman School of Medicine
- Nan Wu
- Center for Data Science, New York University
- Connor Huddleston
- Department of Radiology, NYU Grossman School of Medicine
- Stacey Wolfson
- Department of Radiology, NYU Grossman School of Medicine
- Alexandra Millet
- Department of Radiology, NYU Grossman School of Medicine
- Robin Ehrenpreis
- Department of Radiology, NYU Grossman School of Medicine
- Divya Awal
- Department of Radiology, NYU Grossman School of Medicine
- Cathy Tyma
- Department of Radiology, NYU Grossman School of Medicine
- Naziya Samreen
- Department of Radiology, NYU Grossman School of Medicine
- Yiming Gao
- Department of Radiology, NYU Grossman School of Medicine
- Chloe Chhor
- Department of Radiology, NYU Grossman School of Medicine
- Stacey Gandhi
- Department of Radiology, NYU Grossman School of Medicine
- Cindy Lee
- Department of Radiology, NYU Grossman School of Medicine
- Sheila Kumari-Subaiya
- Department of Radiology, NYU Grossman School of Medicine
- Cindy Leonard
- Department of Radiology, NYU Grossman School of Medicine
- Reyhan Mohammed
- Department of Radiology, NYU Grossman School of Medicine
- Christopher Moczulski
- Department of Radiology, NYU Grossman School of Medicine
- Jaime Altabet
- Department of Radiology, NYU Grossman School of Medicine
- James Babb
- Department of Radiology, NYU Grossman School of Medicine
- Alana Lewin
- Department of Radiology, NYU Grossman School of Medicine
- Beatriu Reig
- Department of Radiology, NYU Grossman School of Medicine
- Linda Moy
- Department of Radiology, NYU Grossman School of Medicine
- Laura Heacock
- Department of Radiology, NYU Grossman School of Medicine
- Krzysztof J. Geras
- Center for Data Science, New York University
- DOI
- https://doi.org/10.1038/s41467-021-26023-2
- Journal volume & issue
-
Vol. 12,
no. 1
pp. 1 – 13
Abstract
Ultrasound is an important imaging modality for the detection and characterization of breast cancer, but it has been noted to have high false-positive rates. Here, the authors present an artificial intelligence system that achieves radiologist-level accuracy in identifying breast cancer in ultrasound imaging.
