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BoXHED 2.0: Scalable boosting of functional data in survival analysis


Mar 23, 2021
Arash Pakbin, Xiaochen Wang, Bobak J. Mortazavi, Donald K. K. Lee

* 9 pages, 2 tables, 2 figures 

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Dynamically Extracting Outcome-Specific Problem Lists from Clinical Notes with Guided Multi-Headed Attention


Jul 25, 2020
Justin Lovelace, Nathan C. Hurley, Adrian D. Haimovich, Bobak J. Mortazavi

* To appear in the proceedings of the Machine Learning for Healthcare Conference (MLHC) 2020. Accepted papers can be viewed at https://www.mlforhc.org/accepted-papers 

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Developing Personalized Models of Blood Pressure Estimation from Wearable Sensors Data Using Minimally-trained Domain Adversarial Neural Networks


Jul 24, 2020
Lida Zhang, Nathan C. Hurley, Bassem Ibrahim, Erica Spatz, Harlan M. Krumholz, Roozbeh Jafari, Bobak J. Mortazavi

* Published at MLHC 2020 

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BoXHED: Boosted eXact Hazard Estimator with Dynamic covariates


Jun 26, 2020
Xiaochen Wang, Arash Pakbin, Bobak J. Mortazavi, Hongyu Zhao, Donald K. K. Lee

* 10 pages, 3 figures, 5 tables 

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Explainable Prediction of Adverse Outcomes Using Clinical Notes


Nov 12, 2019
Justin R. Lovelace, Nathan C. Hurley, Adrian D. Haimovich, Bobak J. Mortazavi

* Machine Learning for Health (ML4H) at NeurIPS 2019 - Extended Abstract 

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A Survey of Challenges and Opportunities in Sensing and Analytics for Cardiovascular Disorders


Aug 12, 2019
Nathan C. Hurley, Erica S. Spatz, Harlan M. Krumholz, Roozbeh Jafari, Bobak J. Mortazavi

* 32 pages, 3 figures, to be submitted to ACM Transactions on Computing for Healthcare (HEALTH), Special Issue on Wearable Technologies for Smart Health 2019 

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Visualization of Emergency Department Clinical Data for Interpretable Patient Phenotyping


Jul 05, 2019
Nathan C. Hurley, Adrian D. Haimovich, R. Andrew Taylor, Bobak J. Mortazavi


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