Paper Citation Record · LEDGER

Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning

As of 8 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2506.14815.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.14815 v1

Coverage vector

measured 40 of 40 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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Reference resolution

40 of 40 outbound references displayed

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External citation measurements

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Outbound references

Observation 829e9f08-57b0-4411-8519-033e9b1ad8fc · outbound

This paper cites A survey on data-efficient algorithms in big data era.

Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning A survey on data-efficient algorithms in big data era

Reference 1

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This paper cites Alves, Elene F.

Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning Alves, Elene F

Reference 2

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This paper cites Support Vector Regression, pages 67–80.

Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning Support Vector Regression, pages 67–80

Reference 3

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Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning Unresolved cited work

Reference 4

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This paper cites Azadifar and A.

Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning Azadifar and A

Reference 5

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Observation 4fd87c91-0ed3-4e49-b0c8-f76004879d67 · outbound

This paper cites Barbosa-Silva, Maria Cristina Gonzalez, Renata M.

Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning Barbosa-Silva, Maria Cristina Gonzalez, Renata M

Reference 6

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This paper cites Bennett, M.C.

Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning Bennett, M.C

Reference 7

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Observation 14c25b89-556d-4960-8602-3731a6b8928c · outbound

This paper cites The rise of artificial intelligence in healthcare applications.

Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning The rise of artificial intelligence in healthcare applications

Reference 8

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This paper cites A compara- tive analysis of gradient boosting algo- rithms.

Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning A compara- tive analysis of gradient boosting algo- rithms

Reference 9

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This paper cites Consis- tency of semi-supervised learning, stochas- tic tug-of-war games, and the p-laplacian.

Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning Consis- tency of semi-supervised learning, stochas- tic tug-of-war games, and the p-laplacian

Reference 10

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Observation 9af2b096-ace1-45e6-a70c-9d33ea3e3426 · outbound

This paper cites Improved spectral convergence rates for graph laplacians on ϵ-graphs and k-nn graphs.

Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning Improved spectral convergence rates for graph laplacians on ϵ-graphs and k-nn graphs

Reference 11

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This paper cites Graphlearning python package, January 2022.

Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning Graphlearning python package, January 2022

Reference 12

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Observation a822878c-fb23-4582-af03-fabf27bbc253 · outbound

This paper cites Nazia Fathima, R.

Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning Nazia Fathima, R

Reference 13

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This paper cites Ran- dom Forests, pages 33–55.

Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning Ran- dom Forests, pages 33–55

Reference 14

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This paper cites Rates of convergence for lapla- cian semi-supervised learning with low la- beling rates.

Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning Rates of convergence for lapla- cian semi-supervised learning with low la- beling rates

Reference 15

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Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning Unresolved cited work

Reference 16

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Observation 2511cfc9-5d99-4beb-8f13-237bfec805af · outbound

This paper cites The effect of sex, age and race on estimating percentage body fat from body mass index: The heritage family study.

Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning The effect of sex, age and race on estimating percentage body fat from body mass index: The heritage family study

Reference 17

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This paper cites Deep Learning.

Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning Deep Learning

Reference 18

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This paper cites An Introduction to Statistical Learn- ing: with Applications in Python.

Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning An Introduction to Statistical Learn- ing: with Applications in Python

Reference 19

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Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning A study of cross-validation and bootstrap for accuracy estimation and model selection

Reference 20

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This paper cites Advances in digital anthropometric body composition assess- ment: neural network algorithm prediction of appendicular lean mass.

Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning Advances in digital anthropometric body composition assess- ment: neural network algorithm prediction of appendicular lean mass

Reference 21

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This paper cites An In- troduction to Statistical Learning: with Applications in R.

Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning An In- troduction to Statistical Learning: with Applications in R

Reference 22

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Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning McCarthy, G

Reference 23

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This paper cites Artificial neural networks to predict future bone mineral density and bone loss rate in japanese postmenopausal women.

Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning Artificial neural networks to predict future bone mineral density and bone loss rate in japanese postmenopausal women

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Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning Dechenaud, Jerome A

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Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning Suykens and Joos Vande- walle

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This paper cites Epub 2023 Dec 23.

Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning Epub 2023 Dec 23

Reference 27

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Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning Marin-Jimenez, C

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Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning van Engelen and Holger H

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Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning Kwok, and Lionel M

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Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning Han, Robert A

Reference 31

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This paper cites Percent body fat is a better predictor of cardiovascular risk factors than body mass index.

Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning Percent body fat is a better predictor of cardiovascular risk factors than body mass index

Reference 32

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This paper cites Recent develop- ments in data science: Comparing linear, ridge and lasso regressions techniques using wine data.

Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning Recent develop- ments in data science: Comparing linear, ridge and lasso regressions techniques using wine data

Reference 33

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This paper cites Kalervo V¨ a¨ an¨ anen and Pirkko L.

Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning Kalervo V¨ a¨ an¨ anen and Pirkko L

Reference 34

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Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning Semi-supervised learning for bone mineral density estimation in hip x-ray images

Reference 39

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Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning Semi-Supervised Learnning 20 with Graphs

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Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning Unresolved cited work

Reference 2020

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Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning Epub 2021 Mar 24

Reference 2021

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Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning Unresolved cited work

Reference 2023

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Predicting Anthropometric Body Composition Variables Using 3D Optical Imaging and Machine Learning Epub 2024 Sep 16

Reference 2024

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