| Comparing clinical judgment with the MySurgeryRisk algorithm for preoperative risk assessment: a pilot usability study M Brennan, S Puri, T Ozrazgat-Baslanti, Z Feng, M Ruppert, ... Surgery 165 (5), 1035-1045, 2019 | 80 | 2019 |
| GraphBTM: Graph enhanced autoencoded variational inference for biterm topic model Q Zhu, Z Feng, X Li Proceedings of the 2018 conference on empirical methods in natural language …, 2018 | 56 | 2018 |
| Performance of a machine learning algorithm using electronic health record data to predict postoperative complications and report on a mobile platform Y Ren, TJ Loftus, S Datta, MM Ruppert, Z Guan, S Miao, B Shickel, Z Feng, ... JAMA Network Open 5 (5), e2211973-e2211973, 2022 | 40 | 2022 |
| Generalized batch normalization: Towards accelerating deep neural networks X Yuan, Z Feng, M Norton, X Li Proceedings of the AAAI conference on artificial intelligence 33 (01), 1682-1689, 2019 | 33 | 2019 |
| Region-wide comprehensive implementation of roguing infected trees, tree replacement, and insecticide applications successfully controls citrus huanglongbing X Yuan, C Chen, RB Bassanezi, F Wu, Z Feng, D Shi, J Li, Y Du, L Zhong, ... Phytopathology® 111 (8), 1361-1368, 2021 | 30 | 2021 |
| Intelligent perioperative system: towards real-time big data analytics in surgery risk assessment Z Feng, RR Bhat, X Yuan, D Freeman, T Baslanti, A Bihorac, X Li 2017 IEEE 15th Intl Conf on Dependable, Autonomic and Secure Computing, 15th …, 2017 | 21 | 2017 |
| Biases in using social media data for public health surveillance: A scoping review Y Zhao, X He, Z Feng, S Bost, M Prosperi, Y Wu, Y Guo, J Bian International Journal of Medical Informatics 164, 104804, 2022 | 9 | 2022 |
| BatmanNet: bi-branch masked graph transformer autoencoder for molecular representation Z Wang, Z Feng, Y Li, B Li, Y Wang, C Sha, M He, X Li Briefings in Bioinformatics 25 (1), bbad400, 2024 | 4 | 2024 |
| Moving from predicting hospital deaths by antibiotic-resistant bloodstream bacteremia toward actionable risk reduction using machine learning on electronic health records I Jun, SN Rich, S Marini, Z Feng, J Bian, JG Morris, M Prosperi AMIA Summits on Translational Science Proceedings 2022, 274, 2022 | 2 | 2022 |
| Heterogeneous treatment effects of metformin on risk of dementia in patients with type 2 diabetes: A longitudinal observational study H Tang, J Guo, CE Shaaban, Z Feng, Y Wu, T Magoc, X Hu, WT Donahoo, ... Alzheimer's & Dementia 20 (2), 975-985, 2024 | 1 | 2024 |
| Evaluating the perceptions of pesticide use, safety, and regulation and identifying common pesticide‐related topics on Twitter I Jun, Z Feng, R Avanasi, RA Brain, M Prosperi, J Bian Integrated environmental assessment and management 19 (6), 1581-1599, 2023 | 1 | 2023 |
| Added value of intraoperative data for predicting postoperative complications: Development and validation of a MySurgeryRisk extension S Datta, TJ Loftus, MM Ruppert, C Giordano, L Adhikari, YC Peng, Y Ren, ... arXiv preprint arXiv:1910.12895, 2019 | 1 | 2019 |
| Real-World Effectiveness of Lung Cancer Screening Using Deep Learning-Based Counterfactual Prediction Z Feng, Z Chen, Y Guo, M Prosperi, H Mehta, D Braithwaite, Y Wu, J Bian MEDINFO 2023—The Future Is Accessible, 419-423, 2024 | | 2024 |
| 483-P: Heterogeneous Treatment Effects of Metformin on the Risk of Dementia in People with Type 2 Diabetes—A Longitudinal Observational Study H TANG, J GUO, C ELIZABETH SHAABAN, Z FENG, Y WU, T MAGOC, ... Diabetes 72 (Supplement_1), 2023 | | 2023 |
| Variational Temporal Deconfounder for Individualized Treatment Effect Estimation with Longitudinal Observational Data Z Feng, M Prosperi, Y Guo, J Bian Research Square, 2023 | | 2023 |
| DR-VIDAL-Doubly Robust Variational Information-theoretic Deep Adversarial Learning for Counterfactual Prediction and Treatment Effect Estimation on Real World Data S Ghosh, Z Feng, J Bian, K Butler, M Prosperi AMIA Annual Symposium Proceedings 2022, 485, 2022 | | 2022 |
| Network PPM. Y Ren, TJ Loftus, S Datta, MM Ruppert, Z Guan, S Miao, B Shickel, Z Feng, ... | | |
