Corrigendum to “Radiomic machine learning for pretreatment assessment of prognostic risk factors for endometrial cancer and its effects on radiologists' decisions of deep myometrial invasion” [Magnetic Resonance Imaging 85 (2022) 161–167]., (S0730725X21001910), (10.1016/j.mri.2021.10.024)

Satoshi Otani; Yuki Himoto; Mizuho Nishio; Koji Fujimoto; Yusaku Moribata; Masahiro Yakami; Yasuhisa Kurata; Junzo Hamanishi; Akihiko Ueda; Sachiko Minamiguchi; Masaki Mandai; Aki Kido

doi:10.1016/j.mri.2021.12.009

Corrigendum to “Radiomic machine learning for pretreatment assessment of prognostic risk factors for endometrial cancer and its effects on radiologists' decisions of deep myometrial invasion” [Magnetic Resonance Imaging 85 (2022) 161–167]., (S0730725X21001910), (10.1016/j.mri.2021.10.024)

Satoshi Otani, Yuki Himoto^*, Mizuho Nishio, Koji Fujimoto, Yusaku Moribata, Masahiro Yakami, Yasuhisa Kurata, Junzo Hamanishi, Akihiko Ueda, Sachiko Minamiguchi, Masaki Mandai, Aki Kido

^*Corresponding author for this work

Diagnostic and Therapeutic Radiology

Research output: Contribution to journal › Comment/debate

2 Scopus citations

Abstract

The authors regret Table 3. The authors would like to remove “(%)” from the original issue. The table below is the correct one. The authors would like to apologise for any inconvenience caused.

Original language	English
Pages (from-to)	119-120
Number of pages	2
Journal	Magnetic Resonance Imaging
Volume	95
DOIs	https://doi.org/10.1016/j.mri.2021.12.009
State	Published - 2023/01

ASJC Scopus subject areas

Biophysics
Biomedical Engineering
Radiology Nuclear Medicine and imaging

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.mri.2021.12.009

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Otani, S., Himoto, Y., Nishio, M., Fujimoto, K., Moribata, Y., Yakami, M., Kurata, Y., Hamanishi, J., Ueda, A., Minamiguchi, S., Mandai, M., & Kido, A. (2023). Corrigendum to “Radiomic machine learning for pretreatment assessment of prognostic risk factors for endometrial cancer and its effects on radiologists' decisions of deep myometrial invasion” [Magnetic Resonance Imaging 85 (2022) 161–167]., (S0730725X21001910), (10.1016/j.mri.2021.10.024). Magnetic Resonance Imaging, 95, 119-120. https://doi.org/10.1016/j.mri.2021.12.009

Otani, Satoshi ; Himoto, Yuki ; Nishio, Mizuho et al. / Corrigendum to “Radiomic machine learning for pretreatment assessment of prognostic risk factors for endometrial cancer and its effects on radiologists' decisions of deep myometrial invasion” [Magnetic Resonance Imaging 85 (2022) 161–167]., (S0730725X21001910), (10.1016/j.mri.2021.10.024). In: Magnetic Resonance Imaging. 2023 ; Vol. 95. pp. 119-120.

@article{e44fe94c0e544eb7b5fef4df1996b53c,

title = "Corrigendum to “Radiomic machine learning for pretreatment assessment of prognostic risk factors for endometrial cancer and its effects on radiologists' decisions of deep myometrial invasion” [Magnetic Resonance Imaging 85 (2022) 161–167]., (S0730725X21001910), (10.1016/j.mri.2021.10.024)",

abstract = "The authors regret Table 3. The authors would like to remove “(%)” from the original issue. The table below is the correct one. The authors would like to apologise for any inconvenience caused.",

author = "Satoshi Otani and Yuki Himoto and Mizuho Nishio and Koji Fujimoto and Yusaku Moribata and Masahiro Yakami and Yasuhisa Kurata and Junzo Hamanishi and Akihiko Ueda and Sachiko Minamiguchi and Masaki Mandai and Aki Kido",

note = "Publisher Copyright: {\textcopyright} 2021 Elsevier Inc.",

year = "2023",

month = jan,

doi = "10.1016/j.mri.2021.12.009",

language = "英語",

volume = "95",

pages = "119--120",

journal = "Magnetic Resonance Imaging",

issn = "0730-725X",

publisher = "Elsevier Inc.",

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Otani, S, Himoto, Y, Nishio, M, Fujimoto, K, Moribata, Y, Yakami, M, Kurata, Y, Hamanishi, J, Ueda, A, Minamiguchi, S, Mandai, M & Kido, A 2023, 'Corrigendum to “Radiomic machine learning for pretreatment assessment of prognostic risk factors for endometrial cancer and its effects on radiologists' decisions of deep myometrial invasion” [Magnetic Resonance Imaging 85 (2022) 161–167]., (S0730725X21001910), (10.1016/j.mri.2021.10.024)', Magnetic Resonance Imaging, vol. 95, pp. 119-120. https://doi.org/10.1016/j.mri.2021.12.009

Corrigendum to “Radiomic machine learning for pretreatment assessment of prognostic risk factors for endometrial cancer and its effects on radiologists' decisions of deep myometrial invasion” [Magnetic Resonance Imaging 85 (2022) 161–167]., (S0730725X21001910), (10.1016/j.mri.2021.10.024). / Otani, Satoshi; Himoto, Yuki; Nishio, Mizuho et al.
In: Magnetic Resonance Imaging, Vol. 95, 01.2023, p. 119-120.

Research output: Contribution to journal › Comment/debate

TY - JOUR

T1 - Corrigendum to “Radiomic machine learning for pretreatment assessment of prognostic risk factors for endometrial cancer and its effects on radiologists' decisions of deep myometrial invasion” [Magnetic Resonance Imaging 85 (2022) 161–167]., (S0730725X21001910), (10.1016/j.mri.2021.10.024)

AU - Otani, Satoshi

AU - Himoto, Yuki

AU - Nishio, Mizuho

AU - Fujimoto, Koji

AU - Moribata, Yusaku

AU - Yakami, Masahiro

AU - Kurata, Yasuhisa

AU - Hamanishi, Junzo

AU - Ueda, Akihiko

AU - Minamiguchi, Sachiko

AU - Mandai, Masaki

AU - Kido, Aki

PY - 2023/1

Y1 - 2023/1

N2 - The authors regret Table 3. The authors would like to remove “(%)” from the original issue. The table below is the correct one. The authors would like to apologise for any inconvenience caused.

AB - The authors regret Table 3. The authors would like to remove “(%)” from the original issue. The table below is the correct one. The authors would like to apologise for any inconvenience caused.

UR - http://www.scopus.com/inward/record.url?scp=85122240224&partnerID=8YFLogxK

U2 - 10.1016/j.mri.2021.12.009

DO - 10.1016/j.mri.2021.12.009

M3 - コメント/討論

C2 - 34996666

AN - SCOPUS:85122240224

SN - 0730-725X

VL - 95

SP - 119

EP - 120

JO - Magnetic Resonance Imaging

JF - Magnetic Resonance Imaging

ER -

Otani S, Himoto Y, Nishio M, Fujimoto K, Moribata Y, Yakami M et al. Corrigendum to “Radiomic machine learning for pretreatment assessment of prognostic risk factors for endometrial cancer and its effects on radiologists' decisions of deep myometrial invasion” [Magnetic Resonance Imaging 85 (2022) 161–167]., (S0730725X21001910), (10.1016/j.mri.2021.10.024). Magnetic Resonance Imaging. 2023 Jan;95:119-120. doi: 10.1016/j.mri.2021.12.009