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2. Cross-sectional assessment of body composition and detection of malnutrition risk in participants with low body mass index and eating disorders using 3D optical surface scans

4. The bioelectrical impedance analysis (BIA) international database: aims, scope, and call for data

6. Quantitative Imaging Principles Improves Medical Image Learning

12. Guidance for assessment of the inflammation etiologic criterion for the GLIM diagnosis of malnutrition: A modified Delphi approach

17. Subcutaneous and visceral fat assessment by DXA and MRI in older adults and children

21. Assessment of clinical measures of total and regional body composition from a commercial 3-dimensional optical body scanner

22. The carbohydrate-insulin model: a physiological perspective on the obesity pandemic

23. A pose‐independent method for accurate and precise body composition from 3D optical scans

25. Predictors of liver fat among children and adolescents from five different ethnic groups

28. Predicting 3D body shape and body composition from conventional 2D photography

31. Sarcopenic obesity research perspectives outlined by the sarcopenic obesity global leadership initiative (SOGLI) – Proceedings from the SOGLI consortium meeting in Rome November 2022

32. Diet Quality and Visceral Adiposity among a Multiethnic Population of Young, Middle, and Older Aged Adults.

33. Detailed 3-dimensional body shape features predict body composition, blood metabolites, and functional strength: the Shape Up! studies

34. Children and Adolescents’ Anthropometrics Body Composition from 3‐D Optical Surface Scans

35. Monitoring body composition change for intervention studies with advancing 3D optical imaging technology in comparison to dual-energy X-ray absorptiometry

41. Sarcopenia: A Time for Action. An SCWD Position Paper

43. Genetic reprogramming of remnant duodenum may contribute to type 2 diabetes improvement after Roux-en-Y gastric bypass

47. Prediction of total and regional body composition from 3D body shape.

49. Weight/height2: Mathematical overview of the world's most widely used adiposity index.

50. Modeling health risks using neural network ensembles.

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