Alejandro Schuler

Publication Activity (10 Years)

Years Active: 2016-2023
Publications (10 Years): 15

Top Topics

Gradient Boosting

Acute Myocardial Infarction

Kernel Ridge Regression

Machine Learning

Top Venues

Publications

David McCoy, Alejandro Schuler, Alan E. Hubbard, Mark J. van der Laan
SuperNOVA: Semi-Parametric Identification and Estimation of Interaction and Effect Modification in Mixed Exposures using Stochastic Interventions in R. J. Open Source Softw. 8 (91) (2023)
Catherine Lee, Brian L. Lawson, Ariana J. Mann, Vincent X. Liu, Laura C. Myers, Alejandro Schuler, Gabriel J. Escobar
Exploratory analysis of novel electronic health record variables for quantification of healthcare delivery strain, prediction of mortality, and prediction of imminent discharge. J. Am. Medical Informatics Assoc. 29 (6) (2022)
Alejandro Schuler, Mark van der Laan
The Selectively Adaptive Lasso. CoRR (2022)
Michael O'Malley, Adam M. Sykulski, Rick Lumpkin, Alejandro Schuler
Multivariate Probabilistic Regression with Natural Gradient Boosting. CoRR (2021)
Ben J. Marafino, Alejandro Schuler, Vincent X. Liu, Art B. Owen, Gabriel J. Escobar, Michael Baiocchi
Integrating Evaluations of Predictive Algorithm-Driven Interventions into Clinical Workflows with the Dynamic Discontinuity Deployment Design. AMIA (2021)
Alejandro Schuler, David Walsh, Diana Hall, Jon Walsh, Charles Fisher
Increasing the efficiency of randomized trial estimates via linear adjustment for a prognostic score. CoRR (2020)
Andrew Ward, Ariana Mann, Jacqueline Vallon, Gabriel J. Escobar, Nicholas Bambos, Alejandro Schuler
Operationally-Informed Hospital-Wide Discharge Prediction Using Machine Learning. HealthCom (2020)
Tony Duan, Avati Anand, Daisy Yi Ding, Khanh K. Thai, Sanjay Basu, Andrew Y. Ng, Alejandro Schuler
NGBoost: Natural Gradient Boosting for Probabilistic Prediction. ICML (2020)
Alejandro Schuler, Aashish Bhardwaj, Vincent X. Liu
Performance metrics for intervention-triggering prediction models do not reflect an expected reduction in outcomes from using the model. CoRR (2020)
Tony Duan, Anand Avati, Daisy Yi Ding, Sanjay Basu, Andrew Y. Ng, Alejandro Schuler
NGBoost: Natural Gradient Boosting for Probabilistic Prediction. CoRR (2019)
Alejandro Schuler, Nigam Shah
General-purpose validation and model selection when estimating individual treatment effects. CoRR (2018)
Jason K. Wang, Jason Hom, Santhosh Balasubramanian, Alejandro Schuler, Nigam H. Shah, Mary K. Goldstein, Michael T. M. Baiocchi, Jonathan H. Chen
An evaluation of clinical order patterns machine-learned from clinician cohorts stratified by patient mortality outcomes. J. Biomed. Informatics 86 (2018)
Jason K. Wang, Alejandro Schuler, Nigam Shah, Jonathan H. Chen
Impact of Clinician Experience on Machine Learned Clinical Order Patterns. AMIA (2017)
Alejandro Schuler, David A. Wulf, Yun Lu, Jennifer M. Baker, Gabriel J. Escobar, Nigam Shah, Vincent X. Liu
A novel propensity modeling approach to estimate the causal impact of acute organ dysfunction on long-term survival in sepsis. CRI (2017)
Alejandro Schuler, Vincent X. Liu, Joe Wan, Alison Callahan, Madeleine Udell, David E. Stark, Nigam H. Shah
Discovering Patient Phenotypes Using Generalized Low Rank Models. PSB (2016)