Developing Artificial Intelligence Models for Extracting Oncologic Outcomes from Japanese Electronic Health Records.

Journal: Advances in therapy
Published Date: Dec 22, 2022

Abstract

INTRODUCTION: A framework that extracts oncological outcomes from large-scale databases using artificial intelligence (AI) is not well established. Thus, we aimed to develop AI models to extract outcomes in patients with lung cancer using unstructured text data from electronic health records of multiple hospitals.

Authors

  • Kenji Araki
    Patient Advocacy Center, University of Miyazaki Hospital, Miyazaki, Japan.
  • Nobuhiro Matsumoto
    Division of Respirology, Rheumatology, Infectious Diseases, and Neurology, Department of Internal Medicine, University of Miyazaki, Miyazaki, Japan.
  • Kanae Togo
    Health & Value, Pfizer Japan Inc., Tokyo, Japan. kanae.togo@pfizer.com.
  • Naohiro Yonemoto
    Department of Biostatistics and Epidemiology, Yokohama City University Graduate School of Medicine and University Medical Center, Yokohama, Japan.
  • Emiko Ohki
    Oncology Medical Affairs, Pfizer Japan Inc, Tokyo, Japan.
  • Linghua Xu
    Health & Value, Pfizer Japan Inc., Tokyo, Japan.
  • Yoshiyuki Hasegawa
    Manufacturing IT Innovation Sector, NTT DATA Corporation, Tokyo, Japan.
  • Daisuke Satoh
  • Ryota Takemoto
    Manufacturing IT Innovation Sector, NTT DATA Corporation, Tokyo, Japan.
  • Taiga Miyazaki
    Division of Respirology, Rheumatology, Infectious Diseases, and Neurology, Department of Internal Medicine, University of Miyazaki, Miyazaki, Japan.

Keywords

External Resources

Popular Topics
Recent Journals