Machine Learning Based Radiomic HPV Phenotyping of Oropharyngeal SCC: A Feasibility Study Using MRI.

Abstract

Authors

• Beomseok Sohn
  Department of Radiology, Research Institute of Radiological Science and Center for Clinical Image Data Science, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Korea.
• Yoon Seong Choi
  Department of Radiology and Research Institute of Radiological Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, South Korea.
• Sung Soo Ahn
  Department of Radiology, Severance Hospital, Research Institute of Radiological Science and Center for Clinical Image Data Science, Yonsei University College of Medicine, Seoul, Korea. sungsoo@yuhs.ac.
• Hwiyoung Kim
  Department of Radiological Science, Yonsei University College of Medicine, Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea. Electronic address: HYKIM82@yuhs.ac.
• Kyunghwa Han
  From the Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, South Korea (S.H.P.); and Department of Radiology, Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, South Korea (K.H.).
• Seung-Koo Lee
  Department of Radiology and Research Institute of Radiological Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, South Korea.
• Jinna Kim
  Department of Radiology and Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, South Korea.

Keywords

External Resources