Zach Shahn

According to our database, Zach Shahn authored at least 11 papers between 2015 and 2021.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2021

Blending Knowledge in Deep Recurrent Networks for Adverse Event Prediction at Hospital Discharge.

Prithwish Chakraborty, James V. Codella, Piyush Madan, Ying Li, Hu Huang, Yoonyoung Park, Chao Yan, Ziqi Zhang, Cheng Gao, Steve Nyemba, Xu Min, Sanjib Basak, Mohamed F. Ghalwash, Zach Shahn, Parthasararathy Suryanarayanan, Italo Buleje, Shannon Harrer, Sarah Miller, Amol Rajmane, Colin Walsh, Jonathan Wanderer, Gigi Y. Yuen-Reed, Kenney Ng, Daby Sow, Bradley A. Malin

CoRR, 2021

G-Net: a Recurrent Network Approach to G-Computation for Counterfactual Prediction Under a Dynamic Treatment Regime.

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

Proceedings of the Machine Learning for Health, 2021

State of the Art Causal Inference in the Presence of Extraneous Covariates: A Simulation Study.

Raluca Cobzaru, Sharon Jiang, Kenney Ng, Stan Finkelstein, Roy Welsch, Zachary Shahn

Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021

2020

Is Deep Reinforcement Learning Ready for Practical Applications in Healthcare? A Sensitivity Analysis of Duel-DDQN for Sepsis Treatment.

Mingyu Lu, Zachary Shahn, Daby Sow, Finale Doshi-Velez, Li-Wei H. Lehman

CoRR, 2020

G-Net: A Deep Learning Approach to G-computation for Counterfactual Outcome Prediction Under Dynamic Treatment Regimes.

Rui Li, Zach Shahn, Jun Li, Mingyu Lu, Prithwish Chakraborty, Daby Sow, Mohamed F. Ghalwash, Li-Wei H. Lehman

CoRR, 2020

Is Deep Reinforcement Learning Ready for Practical Applications in Healthcare? A Sensitivity Analysis of Duel-DDQN for Hemodynamic Management in Sepsis Patients.

Mingyu Lu, Zachary Shahn, Daby Sow, Finale Doshi-Velez, Li-Wei H. Lehman

Proceedings of the AMIA 2020, 2020

Finding Causal Mechanistic Drug-Drug Interactions from Observational Data.

Sanjoy Dey, Ping Zhang, Mohamed F. Ghalwash, Chandramouli Maduri, Daby Sow, Zachary Shahn

Proceedings of the AMIA 2020, 2020

2018

Predicting and Understanding Unexpected Respiratory Decompensation in Critical Care Using Sparse and Heterogeneous Clinical Data.

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

Proceedings of the IEEE International Conference on Healthcare Informatics, 2018

Estimating Causal Multi-Drug-Drug Interaction for Adverse Drug Reactions.

Sanjoy Dey, Ping Zhang, Mohamed F. Ghalwash, Zach Shahn, Daby Sow

Proceedings of the AMIA 2018, 2018

2015

Predicting health outcomes from high-dimensional longitudinal health histories using relational random forests.

Zach Shahn, Patrick B. Ryan, David Madigan

Stat. Anal. Data Min., 2015

Birth month affects lifetime disease risk: a phenome-wide method.

Mary Regina Boland, Zach Shahn, David Madigan, George Hripcsak, Nicholas P. Tatonetti

J. Am. Medical Informatics Assoc., 2015