High-Grade Serous Ovarian Cancer: Use of Machine Learning to Predict Abdominopelvic Recurrence on CT on the Basis of Serial Cancer Antigen 125 Levels.

Abstract

Authors

• Atul B Shinagare
  Center for Evidence-Based Imaging, Brigham and Women's Hospital, Boston, Massachusetts; Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts; Department of Imaging, Dana-Farber Cancer Institute, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts. Electronic address: ashinagare@bwh.harvard.edu.
• Patricia Balthazar
  Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia.
• Ivan K Ip
  Center for Evidence-Based Imaging, Brigham and Women's Hospital, Boston, Massachusetts; Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts.
• Ronilda Lacson
  Center for Evidence-Based Imaging, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, 1620 Tremont St, Boston, MA 02120.
• Joyce Liu
  Harvard Medical School, Boston, Massachusetts; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.
• Nikhil Ramaiya
  Department of Radiology, University Hospitals Cleveland Medical Center, Case Western Reserve University, Cleveland, Ohio.
• Ramin Khorasani
  Center for Evidence-Based Imaging, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, 1620 Tremont St, Boston, MA 02120.

Keywords

External Resources