Ki-67 evaluation using deep-learning model-assisted digital image analysis in breast cancer.

Journal: Histopathology
PMID: 39478421

Abstract

AIMS: To test the efficacy of artificial intelligence (AI)-assisted Ki-67 digital image analysis in invasive breast carcinoma (IBC) with quantitative assessment of AI model performance.

Authors

  • Hirofumi Matsumoto
    Department of Pathology, Nakagami Hospital, Okinawa, Japan.
  • Ryota Miyata
    Department of Mechanical Systems Engineering, University of Ryukyus, Okinawa-ken, Japan.
  • Yuma Tsuruta
    Department of Pathology, Nakagami Hospital, Okinawa, Japan.
  • Norihiro Nakada
    Department of Pathology, Nakagami Hospital, Okinawa, Japan.
  • Ayako Koki
    Department of Breast Surgery, Nakagami Hospital, Okinawa, Japan.
  • Mikiko Unesoko
    Department of Breast Surgery, Nakagami Hospital, Okinawa, Japan.
  • Norie Abe
    Department of Breast Surgery, Nakagami Hospital, Okinawa, Japan.
  • Hisamitsu Zaha
    Department of Breast Surgery, Nakagami Hospital, Okinawa, Japan.

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