Skip to content

Publications

Journal Articles

1.
Glaser Y, Shepherd J, Leong L, Wolfgruber T, Lui LY, Sadowski P, et al. Deep learning predicts all-cause mortality from longitudinal total-body DXA imaging. Commun Med [Internet]. 2022 Aug 16;2. Cite
1.
Leong LT, Wong MC, Glaser Y, Wolfgruber T, Heymsfield SB, Sadwoski P, et al. Quantitative Imaging Principles Improves Medical Image Learning. 2022 Jul 1; Cite
1.
Willingham Jr ML, Spencer S, 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
1.
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;301(3):550–8. Cite
1.
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

Conference Papers

1.
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. In Lugano, Switzerland (Hybrid); 2021. Cite
1.
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 Leuven, Belgium: International Society for Optics and Photonics; 2020. Cite

Presentations

1.
Bunnell A, Valdez D, Wolfgruber T, Altamirano A, Hernandez B, Sadowski P, et al. Abstract P3-04-05: Artificial Intelligence Detects, Classifies, and Describes Lesions in Clinical Breast Ultrasound Images [Internet]. San Antonio Breast Cancer Symposium 2022; 2023 Mar 1 [cited 2023 Mar 15]. Cite
1.
Wong MC, Leong LT, Glaser Y, Sadowski P, Cummings S, Shepherd JA. Artificial Intelligence Predicts Spine and Hip BMD from Whole-Body Dual Energy Xray Absorptiometry Scans. Oral Presentation presented at: International Workshop on Quantitative Musculoskeletal Imaging; 2022 Jun 13; Noordwijk, Netherlands. Cite
1.
Glaser Y, Sehpherd J, Leong L, Wolfgruber T, Lui LY, Cummings SR. Deep-learning-derived all-cause mortality predictor significantly correlated with bone mineral density in males. Poster presented at: International Workshop on Quantitative Musculoskeletal Imaging; 2022 Jun 13; Noordwijk, Netherlands. Cite
1.
Bennett JP, Leong LT, Liu YE, Kelly NN, Glaser Y, Sadowski P, et al. Use of Artificial Intelligence Regional Hallucinations to Correct Body Composition Predictions in Individuals with Metal Implants and Poor Positioning. Oral Presentation presented at: International Workshop on Quantitative Musculoskeletal Imaging; 2022 Jun 13; Noordwijk, Netherlands. Cite
1.
Leong L, Wong MC, Liu YE, Kelly NN, Glaser Y, Sadowski P, et al. Artificial Intelligence Generates Real Analyzable Dual Energy X-ray Absorptiometry Scans from Three-Dimensional Body Scans. Oral Presentation presented at: International Workshop on Quantitative Musculoskeletal Imaging; 2022 Jun 13; Noordwijk, Netherlands. Cite
1.
Leong L. Modular artificial intelligence models for body composition research. Poster presented at: 2022 Biomedical Sciences & Health Disparities Symposium; 2022 Apr 7; Honolulu, HI. Cite Download
1.
Glaser Y, Sadowski P, Wolfgruber T, Lui LY, Cummings S, Shepherd J. Hip Fracture Risk Modelling Using DXA and Artificial Intelligence. Poster presented at: American Society for Bone Mineral and Research Annual Meeting; 2020 Sep 11; Virtual. Cite Download
1.
Omori M. Simulating Microgravity Effects and Changes in Body Shape. Poster presented at: NASA Human Research Program Investigators’ Workshop; 2020 Jan 27; Galvenston, TX. Cite Download