| Dynamic forecasting of Zika epidemics using Google Trends Y Teng, D Bi, G Xie, Y Jin, Y Huang, B Lin, X An, D Feng, Y Tong PloS one 12 (1), e0165085, 2017 | 179 | 2017 |
| Model-informed risk assessment for Zika virus outbreaks in the Asia-Pacific regions Y Teng, D Bi, G Xie, Y Jin, Y Huang, B Lin, X An, Y Tong, D Feng Journal of Infection 74 (5), 484-491, 2017 | 30 | 2017 |
| An integrative analysis reveals a central role of P53 activation via MDM2 in Zika virus infection induced cell death Y Teng, S Liu, X Guo, S Liu, Y Jin, T He, D Bi, P Zhang, B Lin, X An, ... Frontiers in Cellular and Infection Microbiology 7, 327, 2017 | 29 | 2017 |
| Contact reductions from live poultry market closures limit the epidemic of human infections with H7N9 influenza Y Teng, D Bi, X Guo, D Hu, D Feng, Y Tong Journal of Infection 76 (3), 295-304, 2018 | 16 | 2018 |
| Perfusion and permeability MRI predicts future cavernous angioma hemorrhage and growth JY Sone, N Hobson, A Srinath, SG Romanos, Y Li, J Carrión‐Penagos, ... Journal of Magnetic Resonance Imaging 55 (5), 1440-1449, 2022 | 10 | 2022 |
| Perfusion and permeability as diagnostic biomarkers of cavernous angioma with symptomatic hemorrhage JY Sone, Y Li, N Hobson, SG Romanos, A Srinath, SB Lyne, A Shkoukani, ... Journal of Cerebral Blood Flow & Metabolism 41 (11), 2944-2956, 2021 | 7 | 2021 |
| Prediction of chronic kidney disease progression using recurrent neural network and electronic health records Y Zhu, D Bi, M Saunders, Y Ji Scientific Reports 13 (1), 22091, 2023 | 2 | 2023 |
| Circulating Plasma miRNA Homologs in Mice and Humans Reflect Familial Cerebral Cavernous Malformation Disease SG Romanos, A Srinath, Y Li, B Xie, C Chen, Y Li, T Moore, D Bi, JY Sone, ... Translational Stroke Research 14 (4), 513-529, 2023 | 2 | 2023 |
| Predicting the epidemic potential and global diffusion of mosquito-borne diseases using machine learning Y Teng, D Bi, X Guo, R Paul Available at SSRN 3260785, 2018 | 2 | 2018 |
| PAM: Plaid Atoms Model for Bayesian Nonparametric Analysis of Grouped Data D Bi, Y Ji arXiv preprint arXiv:2304.14954, 2023 | 1 | 2023 |
| Plasma metabolites with mechanistic and clinical links to the neurovascular disease cavernous angioma A Srinath, B Xie, Y Li, JY Sone, S Romanos, C Chen, A Sharma, S Polster, ... Communications medicine 3 (1), 35, 2023 | 1 | 2023 |
| Bayesian Sample Size Planning Tool for Phase I Dose-Finding Trials X Lin, J Lyu, S Yuan, D Bi, SJ Wang, Y Ji JCO Precision Oncology 6, e2200046, 2022 | 1 | 2022 |
| A Bayesian Estimator of Sample Size D Bi, Y Ji arXiv preprint arXiv:2404.07923, 2024 | | 2024 |
| Abstract TP12: Changes in Plasma Metabolites Reflect Lesional Iron Content and Permeability Imaging as Monitoring Biomarkers of Hemorrhage in Cavernous Angiomas S Hage, D Bi, D Vera cruz, B Xie, S Kinkade, J Little, A Sidebottom, ... Stroke 55 (Suppl_1), ATP12-ATP12, 2024 | | 2024 |
| BEATS: Bayesian hybrid design with flexible sample size adaptation for time‐to‐event endpoints D Bi, M Liu, J Lin, R Liu Statistics in Medicine 42 (30), 5708-5722, 2023 | | 2023 |
| PAM-HC: A Bayesian Nonparametric Construction of Hybrid Control for Randomized Clinical Trials Using External Data D Bi, T Zhou, W Zhong, Y Ji arXiv preprint arXiv:2310.20087, 2023 | | 2023 |
| Impact of socioeconomics and race on clinical follow-up and trial enrollment and adherence in cerebral cavernous malformation S Hage, M Hagan, D Bi, A Stadnik, J Lee, S Romanos, A Srinath, ... Journal of Stroke and Cerebrovascular Diseases 32 (7), 107167, 2023 | | 2023 |
| Plasma Proteins In Correlation With Lesional Iron Content And Permeability Imaging In Clinical Trial Of Cavernous Angioma With Symptomatic Hemorrhage S Hage, D Bi, Y Li, A Srinath, D Debiasse, S Romanos, R Lightle, ... STROKE 54, 2023 | | 2023 |
| Abstract WP17: Plasma Proteins In Correlation With Lesional Iron Content And Permeability Imaging In Clinical Trial Of Cavernous Angioma With Symptomatic Hemorrhage S Hage, D Bi, Y Li, A Srinath, D Debiasse, S Romanos, R Lightle, ... Stroke 54 (Suppl_1), AWP17-AWP17, 2023 | | 2023 |
| Mutstats: An Ultra-fast Computational Method to Determine Clonal Status of Somatic Mutations D Bi, S Sengupta, T Zhou, Y Ji Journal of Data Science 19 (3), 465-484, 2021 | | 2021 |
Yuan Ji, PhDThe University of ChicagoVerified email at uchicago.edu
