An End-to-End Natural Language Processing System for Automatically Extracting Radiation Therapy Events From Clinical Texts.

Abstract

Authors

• Danielle S Bitterman
  Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, United States.
• Eli Goldner
  Computational Health Informatics Program, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts.
• Sean Finan
  From Research Information Systems and Computing (V.M.C., V.G., S.M.), Partners Healthcare; Boston Children's Hospital Informatics Program (D.D., S.F., G.S.); Harvard Medical School (D.D., S.Y., A.C., M.A.-E.-B., N.A.S., S.M., S.T.W., R.D.); Department of Medicine (S.Y., S.T.W.), Department of Neurosurgery (A.C., M.A.-E.-B., R.D.), Division of Rheumatology, Immunology and Allergy (N.A.S.), and Channing Division of Network Medicine (S.T.W., R.D.), Brigham and Women's Hospital, Boston, MA; Center for Statistical Science (S.Y.), Tsinghua University, Beijing, China; Department of Neurology (S.M.), Massachusetts General Hospital; and Biostatistics (T.C.), Harvard School of Public Health, Boston, MA.
• David Harris
  Boston Children's Hospital, Boston, Massachusetts.
• Eric B Durbin
  University of Kentucky, Lexington, KY.
• Harry Hochheiser
  University of Pittsburgh, Pittsburgh, PA, USA.
• Jeremy L Warner
  Department of Medicine, Brown University, Providence, RI, 02912, United States.
• Raymond H Mak
  Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, United States.
• Timothy Miller
  School of Computing and Information Systems, University of Melbourne, Victoria 3010, Australia.
• Guergana K Savova
  Department of Pediatrics, Children's Hospital of Boston, Boston.

Keywords

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