John A Shepherd
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Explore the profile of John A Shepherd including associated specialties, affiliations and a list of published articles.
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213
Citations
6098
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Recent Articles
1.
Cataldi D, Bennett J, Quon B, Leong L, Kelly T, Binder A, et al.
Sci Rep
. 2025 Feb;
15(1):5839.
PMID: 39966425
Muscle mass and strength are crucial for physiological function and performance in athletes, playing a significant role in maintaining health and optimal athletic performance. Skeletal muscle, which constitutes the majority...
2.
Tian I, Liu J, Wong M, Kelly N, Liu Y, Garber A, et al.
NPJ Digit Med
. 2025 Feb;
8(1):79.
PMID: 39894882
Body composition prediction from 3D optical imagery has previously been studied with linear algorithms. In this study, we present a novel application of deep 3D convolutional graph networks and nonlinear...
3.
Bunnell A, Hung K, Shepherd J, Sadowski P
PLoS One
. 2024 Dec;
19(12):e0315434.
PMID: 39661621
Development of artificial intelligence (AI) for medical imaging demands curation and cleaning of large-scale clinical datasets comprising hundreds of thousands of images. Some modalities, such as mammography, contain highly standardized...
4.
Qiao C, De Lucia Rolfe E, Mak E, Sengupta A, Powell R, Watson L, et al.
NPJ Digit Med
. 2024 Oct;
7(1):298.
PMID: 39443585
Accurate assessment of body composition is essential for evaluating the risk of chronic disease. 3D body shape, obtainable using smartphones, correlates strongly with body composition. We present a novel method...
5.
Bennett J, Wong M, Liu Y, Quon B, Kelly N, Garber A, et al.
Clin Nutr
. 2024 Sep;
43(10):2430-2437.
PMID: 39305753
Background & Aims: Body shape expressed as the trunk-to-leg volume ratio is associated with diabetes and mortality due to the associations between higher adiposity and lower lean mass with Metabolic...
6.
McCarthy C, Wong M, Brown J, Ramirez S, Yang S, Bennett J, et al.
Int J Obes (Lond)
. 2024 Aug;
48(12):1741-1747.
PMID: 39181969
Objective: To evaluate the hypothesis that anthropometric dimensions derived from a person's manifold-regression predicted three-dimensional (3D) humanoid avatar are accurate when compared to their actual circumference, volume, and surface area...
7.
Bennett J, Cataldi D, Liu Y, Kelly N, Quon B, Gonzalez M, et al.
Clin Nutr ESPEN
. 2024 Jul;
63:540-550.
PMID: 39047869
Background & Aims: Bioelectrical impedance analysis (BIA) for body composition estimation is increasingly used in clinical and field settings to guide nutrition and training programs. Due to variations among BIA...
8.
Wilkens L, Castelfranco A, Monroe K, Kristal B, Cheng I, Maskarinec G, et al.
PLoS One
. 2024 Jul;
19(7):e0306606.
PMID: 39024224
Background: We previously developed a prediction score for MRI-quantified abdominal visceral adipose tissue (VAT) based on concurrent measurements of height, body mass index (BMI), and nine blood biomarkers, for optimal...
9.
Wong M, Bennett J, Leong L, Liu Y, Kelly N, Cherry J, et al.
NPJ Microgravity
. 2024 Jun;
10(1):72.
PMID: 38914554
Individuals in isolated and extreme environments can experience debilitating side-effects including significant decreases in fat-free mass (FFM) from disuse and inadequate nutrition. The objective of this study was to determine...
10.
Minetto M, Busso C, Ferraris A, Pietrobelli A, Shepherd J, McCarthy C, et al.
J Vis Exp
. 2024 Jun;
(208).
PMID: 38912781
The body size and composition assessment is commonly included in the routine management of healthy athletes as well as of different types of patients to personalize the training or rehabilitation...