Natural Language Processing and Machine Learning Methods to Characterize Unstructured Patient-Reported Outcomes: Validation Study.

Journal: Journal of medical Internet research
Published Date: Nov 3, 2021

Abstract

BACKGROUND: Assessing patient-reported outcomes (PROs) through interviews or conversations during clinical encounters provides insightful information about survivorship.

Authors

  • Zhaohua Lu
    Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, TN, United States.
  • Jin-Ah Sim
    Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea.
  • Jade X Wang
    Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, TN, United States.
  • Christopher B Forrest
    Roberts Center for Pediatric Research, Children's Hospital of Philadelphia, Philadelphia, PA, United States.
  • Kevin R Krull
    Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, TN, United States.
  • Deokumar Srivastava
    Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, TN, United States.
  • Melissa M Hudson
    Department of Oncology, St. Jude Children's Research Hospital, Memphis, TN, United States.
  • Leslie L Robison
    Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, TN, United States.
  • Justin N Baker
    Department of Oncology, St. Jude Children's Research Hospital, Memphis, TN, United States.
  • I-Chan Huang
    Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, TN, United States.

Keywords

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