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ORCIDLi-Wei H. Lehman
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2020 – today
- 2024
[j4]Feng Wu
, Guoshuai Zhao, Yuerong Zhou, Xueming Qian, Baedorf-Kassis Elias, Li-Wei H. Lehman:
Forecasting Treatment Outcomes Over Time Using Alternating Deep Sequential Models. IEEE Trans. Biomed. Eng. 71(4): 1237-1246 (2024)- [i9]Hong Xiong, Feng Wu, Leon Deng, Megan Su, Li-Wei H. Lehman:
G-Transformer: Counterfactual Outcome Prediction under Dynamic and Time-varying Treatment Regimes. CoRR abs/2406.05504 (2024) - 2023
- [c37]Stephanie M. Hu, Steven Horng, Seth J. Berkowitz, Ruizhi Liao, Rahul G. Krishnan, Li-Wei H. Lehman, Roger G. Mark:
Characterizing the Progression of Pulmonary Edema Severity: Can Pairwise Comparisons in Radiology Reports Help? CinC 2023: 1-4 - [c36]Feng Wu, Guoshuai Zhao, Xueming Qian, Li-Wei H. Lehman:
A Diffusion Model with Contrastive Learning for ICU False Arrhythmia Alarm Reduction. IJCAI 2023: 4912-4920 - [c35]Li-Wei H. Lehman, Benjamin Moody, Harsh Deep, Feng Wu, Hasan Saeed, Lucas McCullum, Diane Perry, Tristan Struja, Qiao Li, Gari D. Clifford, Roger G. Mark:
VTaC: A Benchmark Dataset of Ventricular Tachycardia Alarms from ICU Monitors. NeurIPS 2023 - [i8]Anna Wong, Shu Ge, Nassim Oufattole, Adam Dejl, Megan Su, Ardavan Saeedi, Li-Wei H. Lehman:
A Knowledge Distillation Approach for Sepsis Outcome Prediction from Multivariate Clinical Time Series. CoRR abs/2311.09566 (2023) - 2022
- [c34]Ardavan Saeedi, Yuria Utsumi, Li Sun, Kayhan Batmanghelich, Li-Wei H. Lehman:
Knowledge Distillation via Constrained Variational Inference. AAAI 2022: 8132-8140 - [c33]Lucas McCullum, Hasan Saeed, Benjamin Moody, Diane Perry, Eric Gottlieb, Tom J. Pollard, Xavier Borrat Frigola, Qiao Li, Gari D. Clifford, Roger G. Mark, Li-Wei H. Lehman:
PhysioTag: An Open-Source Platform for Collaborative Annotation of Physiological Waveforms. CinC 2022: 1-4 - [c32]Maximiliano Mollura, Cristian Drudi, Li-Wei H. Lehman, Riccardo Barbieri:
Optimal Fluid And Vasopressor Interventions In Septic ICU Patients Through Reinforcement Learning Model. CinC 2022: 1-4 - [c31]Maximiliano Mollura, Claudia Salerni, Li-Wei H. Lehman, Riccardo Barbieri:
Physiologic Patients' Response to Fluid Administration in Intensive Care Unit. CinC 2022: 1-4 - [c30]Maximiliano Mollura, Cristian Drudi, Li-Wei H. Lehman, Riccardo Barbieri:
A Reinforcement Learning Application for Optimal Fluid and Vasopressor Interventions in Septic ICU Patients. EMBC 2022: 321-324 - [c29]Maximiliano Mollura, Claudia Salerni, Li-Wei H. Lehman, Riccardo Barbieri:
Characterization of Physiologic Patients' Response to Fluid Interventions in the Intensive Care Unit. EMBC 2022: 1402-1405 - [i7]Adam Dejl, Harsh Deep, Jonathan Fei, Ardavan Saeedi, Li-Wei H. Lehman:
Treatment-RSPN: Recurrent Sum-Product Networks for Sequential Treatment Regimes. CoRR abs/2211.07052 (2022) - 2021
- [c28]Maximiliano Mollura, Li-Wei H. Lehman, Riccardo Barbieri:
Assessment of Sepsis in the ICU by Linear and Complex Characterization of Cardiovascular Dynamics. EMBC 2021: 862-865 - [c27]Rui Li, Stephanie M. Hu, Mingyu Lu, Yuria Utsumi, Prithwish Chakraborty, Daby M. Sow, Piyush Madan, Jun Li, Mohamed F. Ghalwash, Zach Shahn, Li-Wei H. Lehman:
G-Net: a Recurrent Network Approach to G-Computation for Counterfactual Prediction Under a Dynamic Treatment Regime. ML4H@NeurIPS 2021: 282-299 - [i6]Ziyu Jia, Youfang Lin, Jing Wang, Xiaojun Ning, Yuanlai He, Ronghao Zhou, Yuhan Zhou, Li-Wei H. Lehman:
Multi-View Spatial-Temporal Graph Convolutional Networks with Domain Generalization for Sleep Stage Classification. CoRR abs/2109.01824 (2021) - 2020
- [c26]Jun Li, Gan Sun, Guoshuai Zhao, Li-Wei H. Lehman:
Robust Low-Rank Discovery of Data-Driven Partial Differential Equations. AAAI 2020: 767-774 - [c25]Mingyu Lu, Zachary Shahn, Daby Sow, Finale Doshi-Velez, Li-Wei H. Lehman:
Is Deep Reinforcement Learning Ready for Practical Applications in Healthcare? A Sensitivity Analysis of Duel-DDQN for Hemodynamic Management in Sepsis Patients. AMIA 2020 - [c24]Maximiliano Mollura, Edoardo Maria Polo, Li-Wei H. Lehman, Riccardo Barbieri:
Assessment of Heart Rate Variability Derived From Blood Pressure Pulse Recordings in Intensive Care Unit Patients. CinC 2020: 1-4 - [c23]Maximiliano Mollura, Stefano Romano, Giulio Mantoan, Li-Wei H. Lehman, Riccardo Barbieri:
Prediction of Septic Shock Onset in ICU by Instantaneous Monitoring of Vital Signs*. EMBC 2020: 2768-2771 - [i5]Rui Li, Zach Shahn, Jun Li, Mingyu Lu, Prithwish Chakraborty, Daby Sow, Mohamed F. Ghalwash, Li-Wei H. Lehman:
G-Net: A Deep Learning Approach to G-computation for Counterfactual Outcome Prediction Under Dynamic Treatment Regimes. CoRR abs/2003.10551 (2020) - [i4]Mingyu Lu, Zachary Shahn, Daby Sow, Finale Doshi-Velez, Li-Wei H. Lehman:
Is Deep Reinforcement Learning Ready for Practical Applications in Healthcare? A Sensitivity Analysis of Duel-DDQN for Sepsis Treatment. CoRR abs/2005.04301 (2020)
2010 – 2019
- 2019
- [c22]Fengyi Tang, Cao Xiao, Fei Wang, Jiayu Zhou, Li-Wei H. Lehman:
Retaining Privileged Information for Multi-Task Learning. KDD 2019: 1369-1377 - [i3]Xuefeng Peng, Yi Ding, David Wihl, Omer Gottesman, Matthieu Komorowski, Li-Wei H. Lehman, Andrew Slavin Ross, Aldo Faisal, Finale Doshi-Velez:
Improving Sepsis Treatment Strategies by Combining Deep and Kernel-Based Reinforcement Learning. CoRR abs/1901.04670 (2019) - 2018
- [j3]Li-Wei H. Lehman, Roger G. Mark, Shamim Nemati:
A Model-Based Machine Learning Approach to Probing Autonomic Regulation From Nonstationary Vital-Sign Time Series. IEEE J. Biomed. Health Informatics 22(1): 56-66 (2018) - [c21]Xuefeng Peng, Yi Ding, David Wihl, Omer Gottesman, Matthieu Komorowski, Li-Wei H. Lehman, Andrew Slavin Ross, Aldo Faisal, Finale Doshi-Velez:
Improving Sepsis Treatment Strategies by Combining Deep and Kernel-Based Reinforcement Learning. AMIA 2018 - [c20]Mohammad M. Ghassemi, Benjamin Moody, Li-Wei H. Lehman, Christopher Song, Qiao Li, Haoqi Sun, M. Brandon Westover, Gari D. Clifford:
You Snooze, You Win: The PhysioNet/Computing in Cardiology Challenge 2018. CinC 2018: 1-4 - [c19]Giovanni Angelotti, Pierandrea Morandini, Li-Wei H. Lehman, Roger G. Mark, Riccardo Barbieri:
The Role of Baroreflex Sensitivity in Acute Hypotensive Episodes Prediction in the Intensive Care Unit. EMBC 2018: 2784-2787 - [c18]Oliver Ren, Alistair E. W. Johnson, Eric P. Lehman, Matthieu Komorowski, Jerome Aboab, Fengyi Tang, Zach Shahn, Daby Sow, Roger G. Mark, Li-Wei H. Lehman:
Predicting and Understanding Unexpected Respiratory Decompensation in Critical Care Using Sparse and Heterogeneous Clinical Data. ICHI 2018: 144-151 - [c17]Eric P. Lehman, Rahul G. Krishnan, Xiaopeng Zhao, Roger G. Mark, Li-Wei H. Lehman:
Representation Learning Approaches to Detect False Arrhythmia Alarms from ECG Dynamics. MLHC 2018: 571-586 - [i2]Omer Gottesman, Fredrik D. Johansson, Joshua Meier, Jack Dent, Donghun Lee, Srivatsan Srinivasan, Linying Zhang, Yi Ding, David Wihl, Xuefeng Peng, Jiayu Yao, Isaac Lage, Christopher Mosch, Li-Wei H. Lehman, Matthieu Komorowski, Aldo Faisal, Leo Anthony Celi, David A. Sontag, Finale Doshi-Velez:
Evaluating Reinforcement Learning Algorithms in Observational Health Settings. CoRR abs/1805.12298 (2018) - [i1]Uma M. Girkar, Ryo Uchimido, Li-Wei H. Lehman, Peter Szolovits, Leo A. Celi, Wei-Hung Weng:
Predicting Blood Pressure Response to Fluid Bolus Therapy Using Attention-Based Neural Networks for Clinical Interpretability. CoRR abs/1812.00699 (2018) - 2017
- [c16]Yang Dai, Sharukh Lokhandwala, William J. Long, Roger G. Mark, Li-Wei H. Lehman:
Phenotyping hypotensive patients in critical care using hospital discharge summaries. BHI 2017: 401-404 - [c15]Aaron Zalewski, William J. Long, Alistair E. W. Johnson, Roger G. Mark, Li-Wei H. Lehman:
Estimating patient's health state using latent structure inferred from clinical time series and text. BHI 2017: 449-452 - [c14]Gari D. Clifford, Chengyu Liu, Benjamin Moody, Li-Wei H. Lehman, Ikaro Silva, Qiao Li, Alistair E. W. Johnson, Roger G. Mark:
AF Classification from a Short Single Lead ECG Recording: the Physionet Computing in Cardiology Challenge 2017. CinC 2017 - 2015
- [j2]Li-Wei H. Lehman, Ryan P. Adams, Louis Mayaud, George B. Moody, Atul Malhotra, Roger G. Mark, Shamim Nemati:
A Physiological Time Series Dynamics-Based Approach to Patient Monitoring and Outcome Prediction. IEEE J. Biomed. Health Informatics 19(3): 1068-1076 (2015) - [c13]Li-Wei H. Lehman, Shamim Nemati, Roger G. Mark:
Hemodynamic Monitoring Using Switching Autoregressive Dynamics of Multivariate Vital Sign Time Series. CinC 2015: 1065-1068 - [c12]Li-Wei H. Lehman, Mohammad M. Ghassemi, Jasper Snoek, Shamim Nemati:
Patient Prognosis from Vital Sign Time Series: Combining Convolutional Neural Networks with a Dynamical Systems Approach. CinC 2015: 1069-1072 - 2014
- [c11]Mohammad M. Ghassemi, Li-Wei H. Lehman, Jasper Snoek, Shamim Nemati:
Global Optimization Approaches for Parameter Tuning in Biomedical Signal Processing: A Focus of Multi-scale Entropy. CinC 2014: 993-996 - [c10]Li-Wei H. Lehman, Shamim Nemati, George B. Moody, Thomas Heldt, Roger G. Mark:
Uncovering Clinical Significance of Vital Sign Dynamics in Critical Care. CinC 2014: 1141-1144 - [c9]Li-Wei H. Lehman, William J. Long, Mohammed Saeed, Roger G. Mark:
Latent topic discovery of clinical concepts from hospital discharge summaries of a heterogeneous patient cohort. EMBC 2014: 1773-1776 - 2013
- [c8]Li-Wei H. Lehman, Shamim Nemati, Ryan P. Adams, George B. Moody, Atul Malhotra, Roger G. Mark:
Tracking progression of patient state of health in critical care using inferred shared dynamics in physiological time series. EMBC 2013: 7072-7075 - [c7]Shamim Nemati, Li-Wei H. Lehman, Ryan P. Adams:
Learning outcome-discriminative dynamics in multivariate physiological cohort time series. EMBC 2013: 7104-7107 - 2012
- [c6]Li-Wei H. Lehman, Mohammed Saeed, William J. Long, Joon Lee, Roger G. Mark:
Risk Stratification of ICU Patients Using Topic Models Inferred from Unstructured Progress Notes. AMIA 2012 - [c5]Li-Wei H. Lehman, Shamim Nemati, Ryan P. Adams, Roger G. Mark:
Discovering shared dynamics in physiological signals: Application to patient monitoring in ICU. EMBC 2012: 5939-5942 - [c4]Shamim Nemati, Li-Wei H. Lehman, Ryan P. Adams, Atul Malhotra:
Discovering shared cardiovascular dynamics within a patient cohort. EMBC 2012: 6526-6529
2000 – 2009
- 2008
- [j1]Ishna Neamatullah, Margaret M. Douglass, Li-Wei H. Lehman, Andrew T. Reisner, Mauricio Villarroel, William J. Long, Peter Szolovits, George B. Moody, Roger G. Mark, Gari D. Clifford:
Automated de-identification of free-text medical records. BMC Medical Informatics Decis. Mak. 8: 32 (2008) - 2006
- [c3]Li-Wei H. Lehman, Steven Lerman:
A Decentralized Network Coordinate System for Robust Internet Distance. ITNG 2006: 631-637 - 2004
- [c2]Li-Wei H. Lehman, Steven Lerman:
PCoord: Network Position Estimation Using Peer-to-Peer Measurements. NCA 2004: 15-24
1990 – 1999
- 1998
- [c1]Li-Wei H. Lehman, Stephen J. Garland, David L. Tennenhouse:
Active Reliable Multicast. INFOCOM 1998: 581-589
Coauthor Index
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