| A new regression model: modal linear regression W Yao, L Li Scandinavian Journal of Statistics 41 (3), 656-671, 2014 | 241 | 2014 |
| Deep learning for brain disorder diagnosis based on fMRI images W Yin, L Li, FX Wu Neurocomputing 469, 332-345, 2022 | 110 | 2022 |
| A comparison of residual diagnosis tools for diagnosing regression models for count data C Feng, L Li, A Sadeghpour BMC Medical Research Methodology 20 (1), 1-21, 2020 | 109* | 2020 |
| Sleep duration and sleep disturbances in association with falls among the middle-aged and older adults in China: a population-based nationwide study SK Essien, CX Feng, W Sun, M Farag, L Li, Y Gao BMC geriatrics 18, 1-14, 2018 | 64 | 2018 |
| Approximating cross-validatory predictive evaluation in Bayesian latent variable models with integrated IS and WAIC L Li, S Qiu, B Zhang, CX Feng Statistics and Computing 26, 881-897, 2016 | 47 | 2016 |
| Predictive analysis methods for human microbiome data with application to Parkinson’s disease M Dong, L Li, M Chen, A Kusalik, W Xu PLoS One 15 (8), e0237779, 2020 | 34 | 2020 |
| Antimicrobial resistance genetic factor identification from whole-genome sequence data using deep feature selection J Shi, Y Yan, MG Links, L Li, JAR Dillon, M Horsch, A Kusalik BMC bioinformatics 20, 1-14, 2019 | 33 | 2019 |
| A semi-supervised autoencoder for autism disease diagnosis W Yin, L Li, FX Wu Neurocomputing 483, 140-147, 2022 | 32 | 2022 |
| Fully Bayesian logistic regression with hyper-LASSO priors for high-dimensional feature selection L Li, W Yao Journal of Statistical Computation and Simulation 88 (14), 2827-2851, 2018 | 25 | 2018 |
| Bayesian hyper-LASSO classification for feature selection with application to endometrial cancer RNA-seq data L Jiang, CMT Greenwood, W Yao, L Li Scientific reports 10 (1), 9747, 2020 | 20 | 2020 |
| A graph attention neural network for diagnosing ASD with fMRI data W Yin, L Li, FX Wu 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2021 | 16 | 2021 |
| Model diagnostics for censored regression via randomized survival probabilities L Li, T Wu, C Feng Statistics in Medicine, 2021 | 16 | 2021 |
| A method for avoiding bias from feature selection with application to naive bayes classification models L Li, RM Neal, J Zhang Bayesian Analysis 3 (1), 171-196, 2008 | 16 | 2008 |
| Robust descriptive discriminant analysis for repeated measures data TT Sajobi, LM Lix, BM Dansu, W Laverty, L Li Computational Statistics & Data Analysis 56 (9), 2782-2794, 2012 | 15 | 2012 |
| Estimating cross‐validatory predictive p‐values with integrated importance sampling for disease mapping models L Li, CX Feng, S Qiu Statistics in medicine 36 (14), 2220-2236, 2017 | 12 | 2017 |
| Modeling zero inflation and overdispersion in the length of hospital stay for patients with ischaemic heart disease CX Feng, L Li Advanced statistical methods in data science, 35-53, 2016 | 10 | 2016 |
| Compressing parameters in Bayesian high-order models with application to logistic sequence models L Li, RM Neal | 10 | 2008 |
| An online Bayesian mixture labelling method by minimizing deviance of classification probabilities to reference labels W Yao, L Li Journal of statistical computation and simulation 84 (2), 310-323, 2014 | 9 | 2014 |
| Bias-corrected hierarchical bayesian classification with a selected subset of high-dimensional features L Li Journal of the American Statistical Association 107 (497), 120-134, 2012 | 8 | 2012 |
| Discriminant analysis for repeated measures data: Effects of mean and covariance misspecification on bias and error in discriminant function coefficients TT Sajobi, LM Lix, L Li, W Laverty Journal of Modern Applied Statistical Methods 10, 571-582, 2011 | 7 | 2011 |
Cindy FengDepartment of Community Health and Epidemiology, Dalhousie Universitydal.ca의 이메일 확인됨
