Correction: Machine learning-based normal tissue complication probability model for predicting albumin-bilirubin (ALBI) grade increase in hepatocellular carcinoma patients
Radiat Oncol. 2023 Mar 15;18(1):53.
doi: 10.1186/s13014-023-02212-9.
1 Division of Radiation Oncology, Department of Radiology, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand. anussara.p@chula.ac.th.
2 Department of Anatomy, Faculty of Dentistry, Mahidol University, Bangkok, Thailand.
3 Division of Radiation Oncology, Department of Radiology, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.
4 Graduate School of Biomedical Science and Engineering, Hokkaido University, Sapporo, Japan.
5 Global Station for Quantum Biomedical Science and Engineering, Global Institute for Cooperative Research and Education, Hokkaido University, Sapporo, Japan.
6 Department of Medical Physics, Hokkaido University Hospital, Sapporo, Japan.
7 Department of Radiation Medical Science and Engineering, Faculty of Medicine, Hokkaido University Graduate School of Medicine, Sapporo, Japan.
8 Research Affairs, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand. sira.sr@chula.ac.th.
9 Center of Excellence in Computational Molecular Biology, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand. sira.sr@chula.ac.th.
10 Center for Artificial Intelligence in Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand. sira.sr@chula.ac.th.