Leveraging natural language processing for efficient information extraction from breast cancer pathology reports: Single-institution study.

Journal: PloS one
PMID: 39965024

Abstract

BACKGROUND: Pathology reports provide important information for accurate diagnosis of cancer and optimal treatment decision making. In particular, breast cancer has known to be the most common cancer in women worldwide.

Authors

  • Phillip Park
    Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology, Sung Kyun Kwan University, Seoul, Korea.
  • Yeonho Choi
    Department of Bio-convergence Engineering, Korea University, Seoul 02841, Republic of Korea.
  • Nayoung Han
    Department of Pathology, National Cancer Center, Goyang, Korea.
  • Ye-Lin Park
    Cancer Data Center, National Cancer Control Institute, National Cancer Center, Goyang, Korea.
  • Juyeon Hwang
    Cancer Data Center, National Cancer Control Institute, National Cancer Center, Goyang, Korea.
  • Heejung Chae
    Cancer Data Center, National Cancer Control Institute, National Cancer Center, Goyang, Korea.
  • Chong Woo Yoo
    Department of Pathology, National Cancer Center, Ilsan, Goyang-si 10408, Gyeonggi-do, Republic of Korea.
  • Kui Son Choi
    Graduate School of Cancer Science and Policy, National Cancer Center, Goyang-si, Gyeonggi-do, Republic of Korea.
  • Hyun-Jin Kim
    Cancer Data Center, National Cancer Control Institute, National Cancer Center, Goyang, Korea.

Keywords

External Resources

Popular Topics
Recent Journals