Generative AI in glioma: Ensuring diversity in training image phenotypes to improve diagnostic performance for IDH mutation prediction.

Abstract

Authors

• Hye Hyeon Moon
  Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
• Jiheon Jeong
  Department of Convergence Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
• Ji Eun Park
  Department of Anatomy and Cell Biology, College of Medicine, Dong-A University, Busan 602-714, Korea.
• Namkug Kim
  Department of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
• Changyong Choi
  Department of Bioengineering, Asan Medical Institute of Convergence Science and Technology, Asan Medical Center, 88 Olympic-Ro 43-Gil Songpa-Gu, Seoul, 05505, South Korea.
• Young-Hoon Kim
  Department of Orthopedic Surgery, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.
• Sang Woo Song
  Department of Neurosurgery, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.
• Chang-Ki Hong
  Department of Neurosurgery, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.
• Jeong Hoon Kim
  Department of Neurosurgery, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.
• Ho Sung Kim
  Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.

Keywords

External Resources