62 publications · sorted by year, newest first.
2025
Deep Learning Enables Large-Scale Shape and Appearance Modeling in Total-Body DXA Imaging
Bunnell A, Cataldi D, Glaser Y, Wolfgruber T, Heymsfield SB, Zonderman AB, Kelly TL, Sadowski P, Shepherd J
Lecture notes in computer science, , 262-276 (2025)
Artificial intelligence-enhanced handheld breast ultrasound for screening: A systematic review of diagnostic test accuracy
Bunnell A, Valdez D, Strand F, Glaser Y, Sadowski P, Shepherd J
PLOS Digital Health, 4, e0001019 (2025)
The gSOS polygenic score is associated with bone density and fracture risk in childhood
Mitchell JA, Bradfield JP, McCormack SE, Chesi A, Kalkwarf HJ, Lappe JM, Oberfield SE, Duren DL, Shepherd J, Hankenson KD, Kelly A, Håkonarson H, Grant SF, Zemel BS
Journal of Bone and Mineral Research, 41, 15-24 (2025)
Prediction of mammographic breast density based on clinical breast ultrasound images using deep learning: a retrospective analysis
Bunnell A, Valdez D, Wolfgruber T, Quon BK, Hung K, Hernandez BY, Seto TB, Killeen J, Miyoshi M, Sadowski P, Shepherd J
The Lancet Regional Health - Americas, 46, 101096 (2025)
3D convolutional deep learning for nonlinear estimation of body composition from whole body morphology
Tian IY, Liu J, Wong MC, Kelly NN, Liu YE, Garber AK, Heymsfield SB, Curless B, Shepherd J
npj Digital Medicine, 8, 79 (2025)
2024
Accurate Prediction of 3D Humanoid Avatars for Anthropometric Modeling
Heymsfield SB, McCarthy C, Wong M, Brown J, Bennett JP, Shepherd J
Current Developments in Nutrition, 8, 103558 (2024)
Prediction of Total and Regional Body Composition from 3D BodyShape
Cipolla R, Qiao C, Rolfe EDL, Brage S, Mak E, Sengupta A, Powell RC, Watson L, Heymsfield SB, Shepherd J, Wareham NJ
Research Square, , (2024)
Abstract 3449: Is AI-enhanced breast ultrasound ready for breast cancer screening in low-resource environments? A systematic review
Bunnell A, Valdez D, Strand F, Glaser Y, Sadowski P, Shepherd J
Cancer Research, 84, 3449 (2024)
3D Convolutional Deep Learning for Nonlinear Estimation of Body Composition from Whole-Body Morphology
Tian IY, Liu J, Wong MC, Kelly NN, Liu Y, Garber AK, Heymsfield SB, Curless B, Shepherd J
Research Square, , (2024)
Accurate prediction of three-dimensional humanoid avatars for anthropometric modeling
McCarthy C, Wong MC, Brown J, Ramirez S, Yang S, Bennett JP, Shepherd J, Heymsfield SB
International Journal of Obesity, 48, 1741-1747 (2024)
Performance of Progressive Generations of GPT on an Exam Designed for Certifying Physicians as Certified Clinical Densitometrists
Valdez D, Bunnell A, Lim SY, Sadowski P, Shepherd J
Journal of Clinical Densitometry, 27, 101480 (2024)
The DIRAC framework: Geometric structure underlies roles of and in combining classifiers
Sniatynski MJ, Shepherd J, Wilkens LR, Hsu DF, Kristal BS
Patterns, 5, 100924 (2024)
Generative deep learning furthers the understanding of local distributions of fat and muscle on body shape and health using 3D surface scans
Leong LT, Wong MC, Liu YE, Glaser Y, Quon BK, Kelly NN, Cataldi D, Sadowski P, Heymsfield SB, Shepherd J
Communications Medicine, 4, 13 (2024)
Learning a Clinically-Relevant Concept Bottleneck for Lesion Detection in Breast Ultrasound
Bunnell A, Glaser Y, Valdez D, Wolfgruber T, Altamirano A, González CZ, Hernandez BY, Sadowski P, Shepherd J
Lecture notes in computer science, , 650-659 (2024)
Prediction of total and regional body composition from 3D body shape
Qiao C, Rolfe EDL, Mak E, Sengupta A, Powell RC, Watson L, Heymsfield SB, Shepherd J, Wareham NJ, Brage S, Cipolla R
npj Digital Medicine, 7, 298 (2024)
2023
Performance of progressive generations of GPT on an exam designed for certifying physicians as Certified Clinical Densitometrists (Preprint)
Valdez D, Bunnell A, Lim SY, Sadowski P, Shepherd J
Deep Learning Furthers the Understanding of Local Distributions of Fat and Muscle on Body Shape and Health Using 3D Surface Scans
Leong LT, Wong MC, Liu YE, Glaser Y, Quon BK, Kelly NN, Cataldi D, Sadowski P, Heymsfield SB, Shepherd J
SSRN Electronic Journal, , (2023)
Supplementary Figure and Table Legends from Using Digital Pathology to Understand Epithelial Characteristics of Benign Breast Disease among Women Undergoing Diagnostic Image-Guided Breast Biopsy
Mullooly M, Puvanesarajah S, Fan S, Pfeiffer RM, Olsson LT, Hada M, Kirk EL, Vacek PM, Weaver DL, Shepherd J, Mahmoudzadeh AP, Wang J, Malkov S, Johnson JM, Hewitt SM, Herschorn SD, Sherman ME, Troester MA, Gierach GL
Supplementary Table 2A from Using Digital Pathology to Understand Epithelial Characteristics of Benign Breast Disease among Women Undergoing Diagnostic Image-Guided Breast Biopsy
Mullooly M, Puvanesarajah S, Fan S, Pfeiffer RM, Olsson LT, Hada M, Kirk EL, Vacek PM, Weaver DL, Shepherd J, Mahmoudzadeh AP, Wang J, Malkov S, Johnson JM, Hewitt SM, Herschorn SD, Sherman ME, Troester MA, Gierach GL
Supplementary Figure 1 from Using Digital Pathology to Understand Epithelial Characteristics of Benign Breast Disease among Women Undergoing Diagnostic Image-Guided Breast Biopsy
Mullooly M, Puvanesarajah S, Fan S, Pfeiffer RM, Olsson LT, Hada M, Kirk EL, Vacek PM, Weaver DL, Shepherd J, Mahmoudzadeh AP, Wang J, Malkov S, Johnson JM, Hewitt SM, Herschorn SD, Sherman ME, Troester MA, Gierach GL
Abstract P3-03-02: Can artificial intelligence derived ultrasound breast density provide comparable breast cancer risk estimates to density derived from mammograms
Valdez D, Bunnell A, Wolfgruber T, Altamirano A, Quon BK, Maskarinec G, Sadowski P, Shepherd J
Cancer Research, 83, P3-03 (2023)
Abstract P3-04-05: Artificial Intelligence Detects, Classifies, and Describes Lesions in Clinical Breast Ultrasound Images
Bunnell A, Valdez D, Wolfgruber T, Altamirano A, Hernandez BY, Sadowski P, Shepherd J
Cancer Research, 83, P3-04 (2023)
Advances in digital anthropometric body composition assessment: neural network algorithm prediction of appendicular lean mass
Marazzato F, McCarthy C, Field RH, Nguyen HTN, Nguyen T, Shepherd J, Tinsley GM, Heymsfield SB
European Journal of Clinical Nutrition, 78, 452-454 (2023)
Automated body composition estimation from device-agnostic 3D optical scans in pediatric populations
Tian IY, Wong MC, Nguyen WM, Kennedy S, McCarthy C, Kelly NN, Liu YE, Garber AK, Heymsfield SB, Curless B, Shepherd J
Clinical Nutrition, 42, 1619-1630 (2023)
Smartphone prediction of skeletal muscle mass: model development and validation in adults
McCarthy C, Tinsley GM, Yang S, Irving BA, Wong MC, Bennett JP, Shepherd J, Heymsfield SB
American Journal of Clinical Nutrition, 117, 794-801 (2023)
2022
Quantitative Imaging Principles Improves Medical Image Learning
Leong LT, Wong M, Glaser Y, Wolfgruber T, Heymsfield SB, Peter S, Shepherd J
arXiv (Cornell University), , (2022)
Deep learning predicts all-cause mortality from longitudinal total-body DXA imaging
Glaser Y, Shepherd J, Leong LT, Wolfgruber T, Lui L, Sadowski P, Cummings SR
Communications Medicine, 2, 102 (2022)
A device‐agnostic shape model for automated body composition estimates from 3D optical scans
Tian IY, Wong MC, Kennedy S, Kelly NN, Liu YE, Garber AK, Heymsfield SB, Curless B, Shepherd J
Medical Physics, 49, 6395-6409 (2022)
2021
Supporting Dataset For Paper: "Ranks underlie outcome of combining classifiers: quantitative roles for Diversity and Accuracy"
Sniatynski MJ, Shepherd J, Ernst T, Wilkens LR, Hsu DF, Kristal BS
Zenodo (CERN European Organization for Nuclear Research), , (2021)
Dual-energy three compartment breast imaging (3CB) for novel compositional biomarkers to improve detection of malignant lesions
Leong LT, Malkov S, Drukker K, Niell BL, Sadowski P, Wolfgruber T, Greenwood H, Joe BN, Kerlikowske K, Giger ML, Shepherd J
Research Square, , (2021)
Evaluating the Accuracy of an Hallucinatory Algorithm to Predict Body Shape Changes from Dieting and Physical Activity
Shepherd J, Wong MC, Tian IY, Liu YE, Kennedy S, LOWE D, Kelly NN, Wong JM, Ebbeling CB, Ludwig DS, Weiss EJ, Curless B, Heymsfield SB
Ranks underlie outcome of combining classifiers: Quantitative roles for and
Sniatynski MJ, Shepherd J, Ernst T, Wilkens LR, Hsu DF, Kristal BS
Patterns, 3, 100415 (2021)
Dual-energy three-compartment breast imaging for compositional biomarkers to improve detection of malignant lesions
Leong LT, Malkov S, Drukker K, Niell BL, Sadowski P, Wolfgruber T, Greenwood H, Joe BN, Kerlikowske K, Giger ML, Shepherd J
Communications Medicine, 1, 29 (2021)
The potential of using artificial intelligence to improve skin cancer diagnoses in Hawai‘i’s multiethnic population
Willingham ML, Spencer SY, Lum C, Sanchez JMN, Burnett T, Shepherd J, Cassel K
Melanoma Research, 31, 504-514 (2021)
A pose‐independent method for accurate and precise body composition from 3D optical scans
Wong MC, Ng BK, Tian IY, Sobhiyeh S, Pagano I, Dechenaud M, Kennedy S, Liu YE, Kelly NN, Chow DC, Garber AK, Maskarinec G, Pujades S, Black MJ, Curless B, Heymsfield SB, Shepherd J
Obesity, 29, 1835-1847 (2021)
Deep Learning Predicts Interval and Screening-detected Cancer from Screening Mammograms: A Case-Case-Control Study in 6369 Women
Zhu X, Wolfgruber T, Leong LT, Jensen MR, Scott CG, Winham SJ, Sadowski P, Vachon CM, Kerlikowske K, Shepherd J
Radiology, 301, 550-558 (2021)
2020
Three compartment breast machine learning model for improving computer-aided detection
Leong LT, Giger ML, Drukker K, Kerlikowske K, Joe BN, Greenwood H, Malkov S, Niell BL, Shepherd J
Fully Automated Pipeline for Body Composition Estimation from 3D Optical Scans using Principal Component Analysis: A Shape Up Study
Sobhiyeh S, Borel N, Dechenaud M, Graham CA, Wong MC, Wolenski PR, Shepherd J, Heymsfield SB
Predicting 3D body shape and body composition from conventional 2D photography
Tian IY, Ng BK, Wong MC, Kennedy S, Hwaung P, Kelly NN, Liu E, Garber AK, Curless B, Heymsfield SB, Shepherd J
Medical Physics, 47, 6232-6245 (2020)
Novel body fat estimation using machine learning and 3-dimensional optical imaging
Harty PS, Sieglinger BA, Heymsfield SB, Shepherd J, Bruner DM, Stratton MT, Tinsley GM
European Journal of Clinical Nutrition, 74, 842-845 (2020)
2019
Metadata and data files supporting the related article: Application of convolutional neural networks to breast biopsies to delineate tissue correlates of mammographic breast density
Mullooly M, Bejnordi BE, Pfeiffer RM, Fan S, Palakal M, Hada M, Vacek PM, Weaver DL, Shepherd J, Fan B, Mahmoudzadeh AP, Wang J, Malkov S, Johnson JM, Herschorn SD, Sprague BL, Hewitt SM, Brinton LA, Karssemeijer N, Laak JVD, Beck AH, Sherman ME, Gierach GL
Figshare, , (2019)
Derived mammographic masking measures based on simulated lesions predict the risk of interval cancer after controlling for known risk factors: a case‐case analysis
Hinton B, Ma L, Mahmoudzadeh AP, Malkov S, Fan B, Greenwood H, Joe BN, Lee V, Strand F, Kerlikowske K, Shepherd J
Medical Physics, 46, 1309-1316 (2019)
Crotch detection on 3D optical scans of human subjects
Sobhiyeh S, Dunkel A, Dechenaud M, Kennedy S, Shepherd J, Heymsfield SB, Wolenski PR
Electronic Imaging, 31, 10-1 (2019)
Hole Filling in 3D Scans for Digital Anthropometric Applications
Sobhiyeh S, Dechenaud M, Dunkel A, LaBorde ML, Kennedy S, Shepherd J, Heymsfield SB, Wolenski PR
Deep learning networks find unique mammographic differences in previous negative mammograms between interval and screen-detected cancers: a case-case study
Hinton B, Ma L, Mahmoudzadeh AP, Malkov S, Fan B, Greenwood H, Joe BN, Lee V, Kerlikowske K, Shepherd J
Cancer Imaging, 19, 41 (2019)
Application of convolutional neural networks to breast biopsies to delineate tissue correlates of mammographic breast density
Mullooly M, Bejnordi BE, Pfeiffer RM, Fan S, Palakal M, Hada M, Vacek PM, Weaver DL, Shepherd J, Fan B, Mahmoudzadeh AP, Wang J, Malkov S, Johnson JM, Herschorn SD, Sprague BL, Hewitt SM, Brinton LA, Karssemeijer N, Laak JVD, Beck AH, Sherman ME, Gierach GL
npj Breast Cancer, 5, 43 (2019)
2017
Shape and Texture Modeling of Hip Bone Density for Fracture Discrimination.
Shepherd J, Mahmoudzadeh AP, Fan B, Chaplin LA, Cootes T, Cauley JA, Cawthon PM, Cummings S, Liu F, Lindner C, Murphy RA, Visser M, Schwartz AV
Research Explorer (The University of Manchester), , (2017)
Abstract 4235: Application of convolutional neural networks to breast biopsies to uncover tissue correlates of mammographic breast density
Mullooly M, Bejnordi BE, Palakal M, Vacek PM, Weaver DL, Shepherd J, Fan B, Mahmoudzadeh AP, Wang J, Johnson JM, Herschorn SD, Sprague BL, Pfeiffer RM, Brinton LA, Sherman ME, Beck A, Gierach GL
Cancer Research, 77, 4235 (2017)
Deep learning and three-compartment breast imaging in breast cancer diagnosis
Drukker K, Huynh BQ, Giger ML, Malkov S, Avila J, Fan B, Joe BN, Kerlikowske K, Drukteinis JS, Kazemi L, Pereira M, Shepherd J
Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE, 10134, 101341F (2017)
Modeling the shape and composition of the human body using dual energy X-ray absorptiometry images
Shepherd J, Ng BK, Fan B, Schwartz AV, Cawthon PM, Cummings SR, Kritchevsky SB, Nevitt M, Santanasto AJ, Cootes T
PLoS ONE, 12, e0175857 (2017)
2014
Statistical appearance modeling of whole-body bone shape and density
Ng BK, Marquino L, Tai V, Sheets C, Mulligan K, Cootes T, Shepherd J
Journal of Orthopaedic Translation, 2, 246-247 (2014)
Roles of biologic breast tissue composition and quantitative image analysis of mammographic images in breast tumor characterization
Drukker K, Giger ML, Duewer F, Malkov S, Flowers CI, Joe BN, Kerlikowske K, Drukteinis JS, Shepherd J
Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE, 9035, 90351U (2014)
Automated Volumetric Breast Density Derived by Statistical Model Approach
Malkov S, Mahmoudzadeh AP, Kerlikowske K, Shepherd J
Lecture notes in computer science, , 257-264 (2014)
Automated volumetric breast density derived by shape and appearance modeling
Malkov S, Kerlikowske K, Shepherd J
Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE, 9034, 90342T (2014)
Mammographic quantitative image analysis and biologic image composition for breast lesion characterization and classification
Drukker K, Duewer F, Giger ML, Malkov S, Flowers CI, Joe BN, Kerlikowske K, Drukteinis JS, Li H, Shepherd J
Medical Physics, 41, 031915 (2014)
