Artificial intelligence to predict the BRAFV600E mutation in patients with thyroid cancer.

Journal: PloS one
Published Date:

Abstract

PURPOSE: To investigate whether a computer-aided diagnosis (CAD) program developed using the deep learning convolutional neural network (CNN) on neck US images can predict the BRAFV600E mutation in thyroid cancer.

Authors

  • Jiyoung Yoon
    Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, South Korea.
  • Eunjung Lee
    Department of Computational Science and Engineering, Yonsei University, Seoul, Korea.
  • Ja Seung Koo
    Department of Pathology, Severance Hospital, Yonsei University, College of Medicine, Seoul, South Korea.
  • Jung Hyun Yoon
    Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, Korea (G.R.K., E.-K.K., J.H.Y., H.J.M., J.Y.K.); Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, Seoul, Korea (S.J.K.); Department of Radiology, Ajou University School of Medicine, Suwon, Korea (E.J.H.); Yonsei University College of Medicine, Seoul, Korea (J.Y.); and Department of Research Affairs, Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, Korea (H.S.L., J.H.H.).
  • Kee-Hyun Nam
    Department of Surgery, Severance Hospital, Yonsei University, College of Medicine, Seoul, South Korea.
  • Jandee Lee
    Department of Surgery, Severance Hospital, Yonsei University, College of Medicine, Seoul, South Korea.
  • Young Suk Jo
    Department of Internal Medicine, Severance Hospital, Yonsei University, College of Medicine, Seoul, South Korea.
  • Hee Jung Moon
    Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, Korea (G.R.K., E.-K.K., J.H.Y., H.J.M., J.Y.K.); Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, Seoul, Korea (S.J.K.); Department of Radiology, Ajou University School of Medicine, Suwon, Korea (E.J.H.); Yonsei University College of Medicine, Seoul, Korea (J.Y.); and Department of Research Affairs, Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, Korea (H.S.L., J.H.H.).
  • Vivian Youngjean Park
    Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
  • Jin Young Kwak
    Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, Korea (G.R.K., E.-K.K., J.H.Y., H.J.M., J.Y.K.); Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, Seoul, Korea (S.J.K.); Department of Radiology, Ajou University School of Medicine, Suwon, Korea (E.J.H.); Yonsei University College of Medicine, Seoul, Korea (J.Y.); and Department of Research Affairs, Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, Korea (H.S.L., J.H.H.). docjin@yuhs.ac.