Corrigendum to “Efficacy of machine learning assisted dental age assessment in local population” [Legal Med. 59 (2022) 102148] (Legal Medicine (2022) 59, (S1344622322001365), (10.1016/j.legalmed.2022.102148))

Te Ju Wu; Chia Ling Tsai; Yin Hua Huang; Tzuo Yau Fan; Yueh Peng Chen

doi:10.1016/j.legalmed.2022.102191

Corrigendum to “Efficacy of machine learning assisted dental age assessment in local population” [Legal Med. 59 (2022) 102148] (Legal Medicine (2022) 59, (S1344622322001365), (10.1016/j.legalmed.2022.102148))

Te Ju Wu
, Chia Ling Tsai
, Yin Hua Huang
, Tzuo Yau Fan
, Yueh Peng Chen^*

^*Corresponding author for this work

Master of Science Degree Program in Innovation for Smart Medicine

Chang Gung University
Ltd.
Chang Gung Memorial Hospital

Research output: Contribution to journal › Comment/debate

Abstract

The authors regret, The IRB approval date in the original “Institutional Review Board Statement” should be corrected to June 14, 2019. The authors would like to apologise for any inconvenience caused.

Original language	English
Article number	102191
Journal	Legal Medicine
Volume	63
DOIs	https://doi.org/10.1016/j.legalmed.2022.102191
State	Published - 07 2023

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© 2022 Elsevier B.V.

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@article{029d556823ac4d29a0a1b54439596ec2,

title = "Corrigendum to “Efficacy of machine learning assisted dental age assessment in local population” [Legal Med. 59 (2022) 102148] (Legal Medicine (2022) 59, (S1344622322001365), (10.1016/j.legalmed.2022.102148))",

abstract = "The authors regret, The IRB approval date in the original “Institutional Review Board Statement” should be corrected to June 14, 2019. The authors would like to apologise for any inconvenience caused.",

author = "Wu, \{Te Ju\} and Tsai, \{Chia Ling\} and Huang, \{Yin Hua\} and Fan, \{Tzuo Yau\} and Chen, \{Yueh Peng\}",

note = "Publisher Copyright: {\textcopyright} 2022 Elsevier B.V.",

year = "2023",

month = jul,

doi = "10.1016/j.legalmed.2022.102191",

language = "英语",

volume = "63",

journal = "Legal Medicine",

issn = "1344-6223",

publisher = "Elsevier B.V.",

}

Corrigendum to “Efficacy of machine learning assisted dental age assessment in local population” [Legal Med. 59 (2022) 102148] (Legal Medicine (2022) 59, (S1344622322001365), (10.1016/j.legalmed.2022.102148)). / Wu, Te Ju; Tsai, Chia Ling; Huang, Yin Hua et al.
In: Legal Medicine, Vol. 63, 102191, 07.2023.

Research output: Contribution to journal › Comment/debate

TY - JOUR

T1 - Corrigendum to “Efficacy of machine learning assisted dental age assessment in local population” [Legal Med. 59 (2022) 102148] (Legal Medicine (2022) 59, (S1344622322001365), (10.1016/j.legalmed.2022.102148))

AU - Wu, Te Ju

AU - Tsai, Chia Ling

AU - Huang, Yin Hua

AU - Fan, Tzuo Yau

AU - Chen, Yueh Peng

PY - 2023/7

Y1 - 2023/7

N2 - The authors regret, The IRB approval date in the original “Institutional Review Board Statement” should be corrected to June 14, 2019. The authors would like to apologise for any inconvenience caused.

AB - The authors regret, The IRB approval date in the original “Institutional Review Board Statement” should be corrected to June 14, 2019. The authors would like to apologise for any inconvenience caused.

UR - https://www.scopus.com/pages/publications/85146075780

U2 - 10.1016/j.legalmed.2022.102191

DO - 10.1016/j.legalmed.2022.102191

M3 - 评论/辩论

C2 - 36610900

AN - SCOPUS:85146075780

SN - 1344-6223

VL - 63

JO - Legal Medicine

JF - Legal Medicine

M1 - 102191

ER -

Corrigendum to “Efficacy of machine learning assisted dental age assessment in local population” [Legal Med. 59 (2022) 102148] (Legal Medicine (2022) 59, (S1344622322001365), (10.1016/j.legalmed.2022.102148))

Abstract

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