Diagnosis prediction of tumours of unknown origin using ImmunoGenius, a machine learning-based expert system for immunohistochemistry profile interpretation.

Journal: Diagnostic pathology
PMID: 33706755

Abstract

BACKGROUND: Immunohistochemistry (IHC) remains the gold standard for the diagnosis of pathological diseases. This technique has been supporting pathologists in making precise decisions regarding differential diagnosis and subtyping, and in creating personalized treatment plans. However, the interpretation of IHC results presents challenges in complicated cases. Furthermore, rapidly increasing amounts of IHC data are making it even harder for pathologists to reach to definitive conclusions.

Authors

  • Yosep Chong
    Department of Hospital Pathology, College of Medicine, The Catholic University of Korea, 271, Cheonbo-ro, Uijeongbu, 11765, Gyeonggi-do, Republic of Korea. ychong@catholic.ac.kr.
  • Nishant Thakur
    Department of Hospital Pathology, College of Medicine, The Catholic University of Korea, 271, Cheonbo-ro, Uijeongbu, 11765, Gyeonggi-do, Republic of Korea.
  • Ji Young Lee
  • Gyoyeon Hwang
    Department of Hospital Pathology, College of Medicine, The Catholic University of Korea, 271, Cheonbo-ro, Uijeongbu, 11765, Gyeonggi-do, Republic of Korea.
  • Myungjin Choi
    Dasom X, Inc., Seoul, Republic of Korea.
  • Yejin Kim
    School of Biomedical Informatics, University of Texas Health, Science Center at Houston, Houston, TX, USA.
  • Hwanjo Yu
    Department of Computer Science and Engineering, POSTECH, Pohang, South Korea and.
  • Mee Yon Cho
    Department of Pathology, Yonsei University, Wonju College of Medicine, Wonju, Republic of Korea.

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