Predicting hematoma expansion in acute spontaneous intracerebral hemorrhage: integrating clinical factors with a multitask deep learning model for non-contrast head CT.

Abstract

Authors

• Hyochul Lee
  Department of Biomedical Sciences, Seoul National University, Seoul, Korea.
• Junhyeok Lee
  Department of Software Convergence, Kyung Hee University, Yongin 17104, Korea.
• Joon Jang
  Department of Biomedical Sciences, Seoul National University, Seoul, South Korea.
• Inpyeong Hwang
  Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea.
• Kyu Sung Choi
  Graduate School of Medical Science and Engineering, Korea Advanced Institute for Science and Technology (KAIST), Daejeon, Republic of Korea.
• Jung Hyun Park
  2Department of Food Science and Technology, Yeungnam University, Gyeongsan, Gyeongsanbuk-do 38541 Republic of Korea.
• Jin Wook Chung
  Department of Radiology, Seoul National University Hospital, 101 Daehak-Ro, Jongno-Gu, Seoul, 03080, Republic of Korea.
• Seung Hong Choi
  From the Graduate School of Medical Science and Engineering (K.H.K., S.H.P.) and Department of Bio and Brain Engineering (S.H.P.), Korea Advanced Institute of Science and Technology, Room 1002, CMS (E16) Building, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea; Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea (S.H.C.); Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea (S.H.C.); and Center for Nanoparticle Research, Institute for Basic Science, Seoul, Republic of Korea (S.H.C.).

Keywords

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