| Machine learning approaches for fracture risk assessment: a comparative analysis of genomic and phenotypic data in 5130 older men Q Wu, F Nasoz, J Jung, B Bhattarai, MV Han Calcified tissue international 107, 353-361, 2020 | 25 | 2020 |
| Genome-wide polygenic risk score for major osteoporotic fractures in postmenopausal women using associated single nucleotide polymorphisms Q Wu, J Jung Journal of Translational Medicine 21 (1), 127, 2023 | 10 | 2023 |
| Machine learning approaches for the prediction of bone mineral density by using genomic and phenotypic data of 5130 older men Q Wu, F Nasoz, J Jung, B Bhattarai, MV Han, RA Greenes, KG Saag Scientific Reports 11 (1), 4482, 2021 | 7 | 2021 |
| Artificial intelligence in fracture detection with different image modalities and data types: A systematic review and meta-analysis J Jung, J Dai, B Liu, Q Wu PLOS Digital Health 3 (1), e0000438, 2024 | 5 | 2024 |
| Shared Genetic Architecture between Muscle and Bone: Identification and Functional Implications of EPDR1, PKDCC, and SPTBN1 J Jung, Q Wu bioRxiv, 2023 | 1 | 2023 |
| Identification of bone mineral density associated genes with shared genetic architectures across multiple tissues: Functional insights for EPDR1, PKDCC, and SPTBN1 J Jung, Q Wu Plos one 19 (4), e0300535, 2024 | | 2024 |
| Revealing the Organ-Specific Expression of SPTBN1 using Single-Cell RNA Sequencing Analysis J Jung, Q Wu bioRxiv, 2023 | | 2023 |
| Contribution of rare variant (s) to the genetic risk score Q Wu, J Jung GENETIC EPIDEMIOLOGY 44 (5), 492-492, 2020 | | 2020 |
| A Statistical Analysis and Machine Learning of Genomic Data J Jung Minnesota State University, Mankato, 2019 | | 2019 |
| The Industrial Relationship in Time-Varying Beta Coefficients in US Industries J Jung | | 2013 |
