| Use of machine learning to develop and evaluate models using preoperative and intraoperative data to identify risks of postoperative complications B Xue, D Li, C Lu, CR King, T Wildes, MS Avidan, T Kannampallil, ... JAMA network open 4 (3), e212240-e212240, 2021 | 134 | 2021 |
| Dynamic cortical connectivity during general anesthesia in healthy volunteers D Li, PE Vlisides, MB Kelz, MS Avidan, GA Mashour Anesthesiology 130 (6), 870-884, 2019 | 66 | 2019 |
| Predicting outcomes in patients undergoing pancreatectomy using wearable technology and machine learning: prospective cohort study H Cos, D Li, G Williams, J Chininis, R Dai, J Zhang, R Srivastava, L Raper, ... Journal of medical Internet research 23 (3), e23595, 2021 | 32 | 2021 |
| Feasibility study of monitoring deterioration of outpatients using multimodal data collected by wearables D Li, J Vaidya, M Wang, B Bush, C Lu, M Kollef, T Bailey ACM Transactions on Computing for Healthcare 1 (1), 1-22, 2020 | 16 | 2020 |
| DeepAlerts: deep learning based multi-horizon alerts for clinical deterioration on oncology hospital wards D Li, PG Lyons, C Lu, M Kollef Proceedings of the AAAI Conference on Artificial Intelligence 34 (01), 743-750, 2020 | 15 | 2020 |
| Integrating static and time-series data in deep recurrent models for oncology early warning systems D Li, P Lyons, J Klaus, B Gage, M Kollef, C Lu Proceedings of the 30th ACM International Conference on Information …, 2021 | 14 | 2021 |
| EEG entropy measures in anesthesia. Front Comput Neurosci 9: 16 Z Liang, Y Wang, X Sun, D Li, LJ Voss, JW Sleigh, S Hagihira, X Li | 10 | 2015 |
| Predicting post-operative complications with wearables: a case study with patients undergoing pancreatic surgery J Zhang, D Li, R Dai, H Cos, GA Williams, L Raper, CW Hammill, C Lu Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2022 | 7 | 2022 |
| Heidy Cos, Gregory A Williams, Lacey Raper, Chet W Hammill, and Chenyang Lu. 2022. Predicting post-operative complications with wearables: a case study with patients undergoing … J Zhang, D Li, R Dai Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2022 | 5 | 2022 |
| 4,300 steps per day prior to surgery are associated with improved outcomes after pancreatectomy H Cos, JGZ Rodríguez, R Srivastava, A Bewley, L Raper, D Li, R Dai, ... HPB 25 (1), 91-99, 2023 | 4 | 2023 |
| Introduction to EMD (Empirical Mode Decomposition) with application to a scientific data D Kim, X Li, D Li, Z Liang, LJ Voss, JW Sleigh Clinical Neurophysiology 119 (11), 2465-2475, 2006 | 3 | 2006 |
| Preoperative levels of physical activity can be increased in pancreatectomy patients via a remotely monitored, telephone-based intervention: A randomized trial JGZ Rodriguez, H Cos, R Srivastava, A Bewley, L Raper, D Li, R Dai, ... Surgery in Practice and Science 15, 100212, 2023 | 2 | 2023 |
| Predicting Intraoperative Hypoxemia with Hybrid Inference Sequence Autoencoder Networks H Liu, M Montana, D Li, C Renfroe, T Kannampallil, C Lu Proceedings of the 31st ACM International Conference on Information …, 2022 | 2 | 2022 |
| Self-explaining Hierarchical Model for Intraoperative Time Series D Li, B Xue, C King, B Fritz, M Avidan, J Abraham, C Lu 2022 IEEE International Conference on Data Mining (ICDM), 1041-1046, 2022 | 1 | 2022 |
| Telemonitoring as Part of Prehabilitation: A Threshold for Daily Step Count that Predicts Improved Outcomes in Pancreatectomy Patients H Cos, R Srivastava, A Bewley, L Raper, JZ Rodriguez, D Li, R Dai, ... HPB 24, S379-S380, 2022 | 1 | 2022 |
| Comparison of deep learning, machine learning, and penalized logistic regression for predicting clinical deterioration in oncology inpatients P Lyons, D Li, C McEvoy, P Westervelt, B Gage, C Lu, MH Kollef D106. STAFFING, TRAINING, AND IMPLEMENTATION TO IMPROVE ICU QUALITY, A7810-A7810, 2020 | 1 | 2020 |
| Predicting clinical deterioration of outpatients using multimodal data collected by wearables D Li, J Vaidya, M Wang, B Bush, C Lu, M Kollef, T Bailey arXiv preprint arXiv:1803.04456, 2018 | 1 | 2018 |
| Readers’ Toolbox D Li, MS Fabus, JW Sleigh, CH Brown IV, A Lewis, J Probert, M Parish, ... | | 2022 |
| Predicting Patient Outcomes with Machine Learning for Diverse Health Data D Li Washington University in St. Louis, 2021 | | 2021 |
| Predicting Intraoperative Hypoxemia with Joint Sequence Autoencoder Networks. H Liu, M Montana, D Li, TG Kannampallil, C Lu CoRR, 2021 | | 2021 |
