| Sample-size determination methodologies for machine learning in medical imaging research: a systematic review I Balki, A Amirabadi, J Levman, AL Martel, Z Emersic, B Meden, ... Canadian Association of Radiologists Journal 70 (4), 344-353, 2019 | 188 | 2019 |
| Partially functional linear regression in high dimensions D Kong, K Xue, F Yao, HH Zhang Biometrika 103 (1), 147-159, 2016 | 166 | 2016 |
| Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease GI Allen, N Amoroso, C Anghel, V Balagurusamy, CJ Bare, D Beaton, ... Alzheimer's & Dementia 12 (6), 645-653, 2016 | 88 | 2016 |
| Early changes in cartilage pericellular matrix micromechanobiology portend the onset of post-traumatic osteoarthritis DR Chery, B Han, Q Li, Y Zhou, SJ Heo, B Kwok, P Chandrasekaran, ... Acta biomaterialia 111, 267-278, 2020 | 82 | 2020 |
| Classical testing in functional linear models D Kong, AM Staicu, A Maity Journal of nonparametric statistics 28 (4), 813-838, 2016 | 76 | 2016 |
| The role of endogenous IFN-β in the regulation of Th17 responses in patients with relapsing-remitting multiple sclerosis Y Tao, X Zhang, M Chopra, MJ Kim, KR Buch, D Kong, J Jin, Y Tang, ... The Journal of Immunology 192 (12), 5610-5617, 2014 | 69 | 2014 |
| FLCRM: Functional linear cox regression model D Kong, JG Ibrahim, E Lee, H Zhu Biometrics 74 (1), 109-117, 2018 | 67 | 2018 |
| FGWAS: functional genome wide association analysis C Huang, P Thompson, Y Wang, Y Yu, J Zhang, D Kong, RR Colen, ... Neuroimage 159, 107-121, 2017 | 51 | 2017 |
| L2RM: Low-rank linear regression models for high-dimensional matrix responses D Kong, B An, J Zhang, H Zhu Journal of the American Statistical Association, 2019 | 50 | 2019 |
| Dietary leucine requirement of older men and women is higher than current recommendations S Szwiega, PB Pencharz, M Rafii, M Lebarron, J Chang, RO Ball, D Kong, ... The American Journal of Clinical Nutrition 113 (2), 410-419, 2021 | 45 | 2021 |
| Decorin regulates cartilage pericellular matrix micromechanobiology DR Chery, B Han, Y Zhou, C Wang, SM Adams, P Chandrasekaran, ... Matrix Biology 96, 1-17, 2021 | 45 | 2021 |
| Single-nucleotide polymorphisms are associated with cognitive decline at Alzheimer's disease conversion within mild cognitive impairment patients E Lee, KS Giovanello, AJ Saykin, F Xie, D Kong, Y Wang, L Yang, ... Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring 8, 86-95, 2017 | 43 | 2017 |
| BFLCRM: A Bayesian functional linear Cox regression model for predicting time to conversion to Alzheimer’s disease E Lee, H Zhu, D Kong, Y Wang, KS Giovanello, JG Ibrahim The annals of applied statistics 9 (4), 2153, 2015 | 36 | 2015 |
| Fully efficient robust estimation, outlier detection and variable selection via penalized regression D Kong, HD Bondell, Y Wu Statistica Sinica, 1031-1052, 2018 | 33 | 2018 |
| Predicting Alzheimer’s disease using combined imaging-whole genome SNP data D Kong, KS Giovanello, Y Wang, W Lin, E Lee, Y Fan, ... Journal of Alzheimer's Disease 46 (3), 695-702, 2015 | 30 | 2015 |
| Differentiated activities of decorin and biglycan in the progression of post-traumatic osteoarthritis B Han, Q Li, C Wang, P Chandrasekaran, Y Zhou, L Qin, XS Liu, ... Osteoarthritis and cartilage 29 (8), 1181-1192, 2021 | 28 | 2021 |
| Ultra‐high dimensional variable selection for doubly robust causal inference D Tang, D Kong, W Pan, L Wang Biometrics 79 (2), 903-914, 2023 | 25* | 2023 |
| Matrix linear discriminant analysis W Hu, W Shen, H Zhou, D Kong Technometrics 62 (2), 196-205, 2020 | 24 | 2020 |
| Predictors of change in suicidal ideation across treatment phases of major depressive disorder: analysis of the STAR* D data CR Weissman, I Hadas, D Yu, B Jones, D Kong, BH Mulsant, ... Neuropsychopharmacology 46 (7), 1293-1299, 2021 | 20 | 2021 |
| Nonparametric matrix response regression with application to brain imaging data analysis W Hu, T Pan, D Kong, W Shen Biometrics 77 (4), 1227-1240, 2021 | 19 | 2021 |
