TY - JOUR
T1 - Correction
T2 - Machine learning-based normal tissue complication probability model for predicting albumin-bilirubin (ALBI) grade increase in hepatocellular carcinoma patients (Radiation Oncology, (2022), 17, 1, (202), 10.1186/s13014-022-02138-8)
AU - Prayongrat, Anussara
AU - Srimaneekarn, Natchalee
AU - Thonglert, Kanokporn
AU - Khorprasert, Chonlakiet
AU - Amornwichet, Napapat
AU - Alisanant, Petch
AU - Shirato, Hiroki
AU - Kobashi, Keiji
AU - Sriswasdi, Sira
N1 - Publisher Copyright:
© 2023 The Author(s).
PY - 2023/12
Y1 - 2023/12
N2 - After publication of this article [1], the authors reported that Sira Sriswasdi should have been denoted as co-corresponding author. The original article [1] has been corrected.
AB - After publication of this article [1], the authors reported that Sira Sriswasdi should have been denoted as co-corresponding author. The original article [1] has been corrected.
UR - http://www.scopus.com/inward/record.url?scp=85150312095&partnerID=8YFLogxK
U2 - 10.1186/s13014-023-02212-9
DO - 10.1186/s13014-023-02212-9
M3 - Comment/debate
C2 - 36922889
AN - SCOPUS:85150312095
SN - 1748-717X
VL - 18
JO - Radiation Oncology
JF - Radiation Oncology
IS - 1
M1 - 53
ER -