TY - JOUR
T1 - Correction to
T2 - Predictive modeling for 14-day unplanned hospital readmission risk by using machine learning algorithms (BMC Medical Informatics and Decision Making, (2021), 21, 1, (288), 10.1186/s12911-021-01639-y)
AU - Lo, Yu Tai
AU - Liao, Jay Chiehen
AU - Chen, Mei Hua
AU - Chang, Chia Ming
AU - Li, Cheng Te
N1 - Publisher Copyright:
© The Author(s) 2022.
PY - 2022/12
Y1 - 2022/12
N2 - Following publication of the original article [1], the following errors were reported: 1) Jah Chiehen Liao’s name was misspelled as ‘Jay Chiehen Liao’ 2) A note marking Yu-Tai Lo and Jay Chiehen Liao as co-first authors was missing 3) A grant number was missing in the Acknowledgement declaration The correct authorship list is given in this Correction article and the corrected Acknowledgement declaration is given below, with the missing number in bold: Acknowledgements We thank the nursing supervisor of discharge planning Ms. Hsiu-Hua Lee, discharge planning nurses, and the information technicians at National Cheng Kung University Hospital for helping us collect data from patients’ medical records. This work is supported by the Ministry of Science and Technology (MOST) of Taiwan under grants 109-2636-E-006-017 (MOST Young Scholar Fellowship), 110-2221-E-006-001, 110-2221-E-006- 136-MY3, and 110-2634-F-002-051. The original article [1] has been updated.
AB - Following publication of the original article [1], the following errors were reported: 1) Jah Chiehen Liao’s name was misspelled as ‘Jay Chiehen Liao’ 2) A note marking Yu-Tai Lo and Jay Chiehen Liao as co-first authors was missing 3) A grant number was missing in the Acknowledgement declaration The correct authorship list is given in this Correction article and the corrected Acknowledgement declaration is given below, with the missing number in bold: Acknowledgements We thank the nursing supervisor of discharge planning Ms. Hsiu-Hua Lee, discharge planning nurses, and the information technicians at National Cheng Kung University Hospital for helping us collect data from patients’ medical records. This work is supported by the Ministry of Science and Technology (MOST) of Taiwan under grants 109-2636-E-006-017 (MOST Young Scholar Fellowship), 110-2221-E-006-001, 110-2221-E-006- 136-MY3, and 110-2634-F-002-051. The original article [1] has been updated.
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U2 - 10.1186/s12911-022-01804-x
DO - 10.1186/s12911-022-01804-x
M3 - Comment/debate
C2 - 35337321
AN - SCOPUS:85127294834
SN - 1472-6947
VL - 22
JO - BMC Medical Informatics and Decision Making
JF - BMC Medical Informatics and Decision Making
IS - 1
M1 - 73
ER -