| A Bayesian credible subgroups approach to identifying patient subgroups with positive treatment effects PM Schnell, Q Tang, WW Offen, BP Carlin Biometrics 72 (4), 1026-1036, 2016 | 67 | 2016 |
| ABT-126 monotherapy in mild-to-moderate Alzheimer’s dementia: randomized double-blind, placebo and active controlled adaptive trial and open-label extension LM Gault, RA Lenz, CW Ritchie, A Meier, AA Othman, Q Tang, S Berry, ... Alzheimer's research & therapy 8, 1-13, 2016 | 42 | 2016 |
| APOE-ɛ4 Carrier Status and Donepezil Response in Patients with Alzheimer’s Disease JF Waring, Q Tang, WZ Robieson, DP King, U Das, J Dubow, S Dutta, ... Journal of Alzheimer's Disease 47 (1), 137-148, 2015 | 39 | 2015 |
| Efficacy and safety of ABT-126 in subjects with mild-to-moderate Alzheimer’s disease on stable doses of acetylcholinesterase inhibitors: a randomized, double-blind, placebo … H Florian, A Meier, S Gauthier, S Lipschitz, Y Lin, Q Tang, AA Othman, ... Journal of Alzheimer's Disease 51 (4), 1237-1247, 2016 | 36 | 2016 |
| Predicting phase 3 clinical trial results by modeling phase 2 clinical trial subject level data using deep learning Y Qi, Q Tang Machine Learning for Healthcare Conference, 288-303, 2019 | 22 | 2019 |
| Subgroup inference for multiple treatments and multiple endpoints in an Alzheimer’s disease treatment trial P Schnell, Q Tang, P Müller, BP Carlin | 17 | 2017 |
| Multiplicity-adjusted semiparametric benefiting subgroup identification in clinical trials PM Schnell, P Müller, Q Tang, BP Carlin Clinical Trials 15 (1), 75-86, 2018 | 12 | 2018 |
| O1‐05‐02: EFFICACY AND SAFETY OF THE ALPHA7 AGONIST ABT‐126 AS A MONOTHERAPY TREATMENT IN MILD‐TO‐MODERATE ALZHEIMER'S DEMENTIA: RESULTS OF A PHASE 2B TRIAL A Othman, A Meier, CW Ritchie, H Florian, LM Gault, Q Tang Alzheimer's & Dementia 10, P137-P137, 2014 | 12 | 2014 |
| Predictive probability methods for interim monitoring in clinical trials with longitudinal outcomes M Zhou, Q Tang, L Lang, J Xing, K Tatsuoka Statistics in Medicine 37 (14), 2187-2207, 2018 | 11 | 2018 |
| Enhancing the sample average approximation method with U designs Q Tang, PZG Qian Biometrika 97 (4), 947-960, 2010 | 9 | 2010 |
| A Bayesian Meta-analysis Method for Estimating Risk Difference of Rare Events Y Tang, Q Tang, Y Yu, S Wen Journal of Biopharmacuetical Statistics, 2017 | 8 | 2017 |
| P4‐353: A PHASE 2 TRIAL OF THE EFFICACY AND SAFETY OF THE ALPHA7 AGONIST ABT‐126 AS AN ADD‐ON TREATMENT IN MILD‐TO‐MODERATE ALZHEIMER'S DEMENTIA LM Gault, A Meier, H Florian, S Gauthier, Y Lin, Q Tang, A Othman Alzheimer's & Dementia 10, P917-P918, 2014 | 7 | 2014 |
| Random group variance estimators for survey data with random hot deck imputation J Shao, Q Tang Journal of Official Statistics 27 (3), 507, 2011 | 7 | 2011 |
| Real-world evidence in drug development and evaluation H Yang, B Yu CRC Press, 2021 | 6 | 2021 |
| An integrative approach of digital image analysis and transcriptome profiling to explore potential predictive biomarkers for TGFβ blockade therapy R Pomponio, Q Tang, A Mei, A Caron, B Coulibaly, J Theilhaber, ... Acta Pharmaceutica Sinica B 12 (9), 3594-3601, 2022 | 5 | 2022 |
| Bayesian applications in pharmaceutical development M Lakshminarayanan, F Natanegara CRC Press, 2019 | 5 | 2019 |
| 006 Therapeutic response guided dosing strategy to optimize long-term adalimumab treatment in patients with hidradenitis suppurativa: integrated results from the PIONEER phase … W Gulliver, MM Okun, A Martorell, Z Geng, X Huang, Q Tang, DA Williams, ... Journal of Investigative Dermatology 136 (9), S161, 2016 | 4* | 2016 |
| Image translation based nuclei segmentation for immunohistochemistry images R Trullo, QA Bui, Q Tang, R Olfati-Saber MICCAI Workshop on Deep Generative Models, 87-96, 2022 | 2 | 2022 |
| Systems and methods for predicting expression levels AL Bauchet, A Mei, Q Tang US Patent App. 17/911,841, 2023 | 1 | 2023 |
| Residual semi-recurrent neural networks Q Tang, Y Qi US Patent 11,625,589, 2023 | 1 | 2023 |
Bradley P. CarlinPharmaLex - USVerified email at counterpointstat.com
