npj Digital Medicine (Jul 2020)
Author Correction: PENet—a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging
- Shih-Cheng Huang,
- Tanay Kothari,
- Imon Banerjee,
- Chris Chute,
- Robyn L. Ball,
- Norah Borus,
- Andrew Huang,
- Bhavik N. Patel,
- Pranav Rajpurkar,
- Jeremy Irvin,
- Jared Dunnmon,
- Joseph Bledsoe,
- Katie Shpanskaya,
- Abhay Dhaliwal,
- Roham Zamanian,
- Andrew Y. Ng,
- Matthew P. Lungren
Affiliations
- Shih-Cheng Huang
- Department of Biomedical Data Science, Stanford University
- Tanay Kothari
- Department of Computer Science, Stanford University
- Imon Banerjee
- Department of Biomedical Data Science, Stanford University
- Chris Chute
- Department of Computer Science, Stanford University
- Robyn L. Ball
- Center for Artificial Intelligence in Medicine & Imaging, Stanford University
- Norah Borus
- Department of Computer Science, Stanford University
- Andrew Huang
- Department of Computer Science, Stanford University
- Bhavik N. Patel
- Department of Radiology, Stanford University
- Pranav Rajpurkar
- Department of Computer Science, Stanford University
- Jeremy Irvin
- Department of Computer Science, Stanford University
- Jared Dunnmon
- Department of Radiology, Stanford University
- Joseph Bledsoe
- Department of Emergency Medicine, Intermountain Medical Center
- Katie Shpanskaya
- Department of Radiology, Stanford University
- Abhay Dhaliwal
- Michigan State University, College of Human Medicine
- Roham Zamanian
- Department of Pulmonary Critical Care Medicine, Stanford University
- Andrew Y. Ng
- Department of Computer Science, Stanford University
- Matthew P. Lungren
- Department of Biomedical Data Science, Stanford University
- DOI
- https://doi.org/10.1038/s41746-020-00310-6
- Journal volume & issue
-
Vol. 3,
no. 1
pp. 1 – 1
Abstract
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
