Publications

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Hinton B, Shepherd JA, Kerlikowske K, Joe BN, Greenwood HI, Ma L. Deep learning methods aid in predicting risk of interval cancer. In: Krupinski EA, editor. 14th International Workshop on Breast Imaging (IWBI 2018) [Internet]. Atlanta, United States: SPIE; 2018 [cited 2019 Jul 24]. p. 71. Cite Download
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Hinton B, Ma L, Mahmoudzadeh AP, Malkov S, Fan B, Greenwood H, et al. Deep learning networks find unique mammographic differences in previous negative mammograms between interval and screen-detected cancers: a case-case study. Cancer Imaging [Internet]. 2019 Jun 22 [cited 2019 Jul 24];19(1):41. Cite
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Shepherd JA. Principles and Applications in Artificial Intelligence to Research and Clinical Care for Bone and Mineral Research. In Virtual; 2020. Cite
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Shepherd J. Approaches to analyzing DXA data using convolution neural networks. International Society for Clinical Densitometry Annual Meeting; 2020; Minneapolis, MN. Cite
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Omori M, Bennett J, Wong M, Sadowski P, Shepherd J. A Step Towards Measuring Body Composition in Space. NASA’s Human Research Program Investigators’ Workshop; 2020. Cite Download
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Omori M. Simulating Microgravity Effects and Changes in Body Shape. NASA Human Research Program Investigators’ Workshop; 2020 Jan 27; Galvenston, TX. Cite Download
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Leong L, Giger M, Drukker K, Kerlikowske K, Joe B, Greenwood H, et al. Three compartment breast machine learning model for improving computer-aided detection. In: 15th International Workshop on Breast Imaging (IWBI2020) [Internet]. Leuven, Belgium; 2020. Cite
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Glaser Y, Sadowski P, Wolfgruber T, Lui LY, Cummings S, Shepherd J. Hip Fracture Risk Modelling Using DXA and Artificial Intelligence. American Society for Bone Mineral and Research Annual Meeting; 2020 Sep 11; Virtual. Cite Download
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Leong LT, Malkov S, Drukker K, Niell BL, Sadowski P, Wolfgruber T, et al. Dual-energy three-compartment breast imaging for compositional biomarkers to improve detection of malignant lesions. Communications Medicine [Internet]. 2021 Aug 31;1(1):29. Cite
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Leong L, Wong M, Piazza M, Garry S, Heymsfield S, Shepherd J. Creating Accurate Representations of DXA Scans from 3D Optical Body Surface Scans for Arbitrary Regional Body Composition Analysis. 3DBODY.TECH Conference & Expo; 2021 Oct 19; Lugano, Switzerland (Hybrid). Cite
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Willingham Jr ML, Spencer SY, Lum CA, Sanchez JMN, Burnett T, Shepherd J, et al. The potential of using artificial intelligence to improve skin cancer diagnoses in Hawai'i's multiethnic population. Melanoma Research [Internet]. 2021 Dec 1;31(6):504–14. Cite
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Zhu X, Wolfgruber TK, Leong L, Jensen M, Scott C, Winham S, et al. Deep Learning Predicts Interval and Screening-detected Cancer from Screening Mammograms: A Case-Case-Control Study in 6369 Women. Radiology [Internet]. 2021 Dec 1 [cited 2022 Mar 24];301(3):550–8. Cite