Prediction of prognosis using artificial intelligence-based histopathological image analysis in patients with soft tissue sarcomas.

Journal: Cancer medicine
PMID: 38800990

Abstract

BACKGROUND: Prompt histopathological diagnosis with accuracy is required for soft tissue sarcomas (STSs) which are still challenging. In addition, the advances in artificial intelligence (AI) along with the development of pathology slides digitization may empower the demand for the prediction of behavior of STSs. In this article, we explored the application of deep learning for prediction of prognosis from histopathological images in patients with STS.

Authors

  • Tomohito Hagi
    Department of Orthopedic Surgery, Mie University Graduate School of Medicine, Tsu, Japan.
  • Tomoki Nakamura
    Department of Orthopedic Surgery, Mie University Graduate School of Medicine, Tsu, Japan.
  • Hiroto Yuasa
    Department of Oncologic Pathology, Mie University Graduate School of Medicine, Tsu, Japan.
  • Katsunori Uchida
    Department of Oncologic Pathology, Mie University Graduate School of Medicine, Tsu, Japan.
  • Kunihiro Asanuma
    Department of Orthopedic Surgery, Mie University Graduate School of Medicine, Tsu, Japan.
  • Akihiro Sudo
    1 Department of Orthopaedic Surgery, Mie University Graduate School of Medicine, Mie, Japan.
  • Tetsushi Wakabayahsi
    Department of Information Engineering, Mie University Graduate School of Engineering, Tsu, Japan.
  • Kento Morita
    School of Electrical Information Communication Engineering, College of Science and Engineering, Kanazawa University Kanazawa Japan.

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