Advancement of accuracy and precision to integrate AI tools in clinical practice. Re. “Evaluation of a fully automated computed tomography image segmentation method for fast and accurate body composition measurements”

J. L.A. van Vugt; K. Popuri; M. F. Beg

doi:10.1016/j.nut.2025.112841

Advancement of accuracy and precision to integrate AI tools in clinical practice. Re. “Evaluation of a fully automated computed tomography image segmentation method for fast and accurate body composition measurements”

J. L.A. van Vugt^*, K. Popuri, M. F. Beg

^*Corresponding author for this work

Surgery

Research output: Contribution to journal › Comment/Letter to the editor › Academic › peer-review

Original language	English
Article number	112841
Journal	Nutrition
Volume	139
DOIs	https://doi.org/10.1016/j.nut.2025.112841
Publication status	Published - Nov 2025

UN SDGs

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

Access to Document

10.1016/j.nut.2025.112841

Cite this

@article{910fb80eef3248b58d0a68434338fb7b,

title = "Advancement of accuracy and precision to integrate AI tools in clinical practice. Re. “Evaluation of a fully automated computed tomography image segmentation method for fast and accurate body composition measurements”",

author = "van Vugt, \{J. L.A.\} and K. Popuri and Beg, \{M. F.\}",

year = "2025",

month = nov,

doi = "10.1016/j.nut.2025.112841",

language = "English",

volume = "139",

journal = "Nutrition",

issn = "0899-9007",

publisher = "Elsevier Inc.",

}

Advancement of accuracy and precision to integrate AI tools in clinical practice. Re. “Evaluation of a fully automated computed tomography image segmentation method for fast and accurate body composition measurements”. / van Vugt, J. L.A.; Popuri, K.; Beg, M. F.
In: Nutrition, Vol. 139, 112841, 11.2025.

Research output: Contribution to journal › Comment/Letter to the editor › Academic › peer-review

TY - JOUR

T1 - Advancement of accuracy and precision to integrate AI tools in clinical practice. Re. “Evaluation of a fully automated computed tomography image segmentation method for fast and accurate body composition measurements”

AU - van Vugt, J. L.A.

AU - Popuri, K.

AU - Beg, M. F.

PY - 2025/11

Y1 - 2025/11

UR - https://www.scopus.com/pages/publications/105014774610

U2 - 10.1016/j.nut.2025.112841

DO - 10.1016/j.nut.2025.112841

M3 - Comment/Letter to the editor

C2 - 40664590

AN - SCOPUS:105014774610

SN - 0899-9007

VL - 139

JO - Nutrition

JF - Nutrition

M1 - 112841

ER -

Advancement of accuracy and precision to integrate AI tools in clinical practice. Re. “Evaluation of a fully automated computed tomography image segmentation method for fast and accurate body composition measurements”

UN SDGs

Access to Document

Other files and links

Embargoed Document

Cite this